diff --git a/.dockerignore b/.dockerignore
deleted file mode 100644
index 0300decc..00000000
--- a/.dockerignore
+++ /dev/null
@@ -1 +0,0 @@
-**/.venv
diff --git a/.github/workflows/pytype-neuron.yaml b/.github/workflows/pytype-base.yaml
similarity index 90%
rename from .github/workflows/pytype-neuron.yaml
rename to .github/workflows/pytype-base.yaml
index fb9a9480..91761e63 100644
--- a/.github/workflows/pytype-neuron.yaml
+++ b/.github/workflows/pytype-base.yaml
@@ -15,6 +15,6 @@ jobs:
         uses: astral-sh/setup-uv@v3
 
       - name: Test Types
-        working-directory: neuron
+        working-directory: base
         run: |
           uv run pytype
diff --git a/.gitignore b/.gitignore
index f1ab62af..1019162b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -161,7 +161,4 @@ cython_debug/
 .idea/
 
 huggingface/
-pip/
-miner/model/
-miner/baseline_cache.json
 validator/compose.yaml
diff --git a/README.md b/README.md
index 86f987f9..bd717ff5 100644
--- a/README.md
+++ b/README.md
@@ -129,9 +129,7 @@ uv run submit_model \
     --netuid {netuid} \
     --subtensor.network finney \
     --wallet.name {wallet} \
-    --wallet.hotkey {hotkey} \
-    --logging.trace \
-    --logging.debug
+    --wallet.hotkey {hotkey}
 ```
 5. Follow the interactive prompts to submit the repository link, revision, and contest to participate in
 6. Optionally, benchmark your submission locally before submitting (make sure you have the right hardware e.g. NVIDIA GeForce RTX 4090). uv and huggingface are required for benchmarking:
@@ -150,7 +148,7 @@ If your hardware is not accessed within a container(as in, can use Docker), then
 
 To get started, go to the `validator`, and create a `.env` file with the following contents:
 ```
-VALIDATOR_ARGS=--netuid {netuid} --subtensor.network {network} --wallet.name {wallet} --wallet.hotkey {hotkey} --logging.trace --logging.debug
+VALIDATOR_ARGS=--netuid {netuid} --subtensor.network {network} --wallet.name {wallet} --wallet.hotkey {hotkey}
 VALIDATOR_HOTKEY_SS58_ADDRESS={ss58-address}
 ```
 
@@ -201,8 +199,6 @@ In the another pod/container without a GPU, to run the scoring validator, clone
         --subtensor.network {network} \
         --wallet.name {wallet} \
         --wallet.hotkey {hotkey} \
-        --logging.trace \
-        --logging.debug \
         --benchmarker_api {API component routes, space separated if multiple}
 ```
 
diff --git a/miner/miner/__init__.py b/base/base/__init__.py
similarity index 100%
rename from miner/miner/__init__.py
rename to base/base/__init__.py
diff --git a/base/base/checkpoint.py b/base/base/checkpoint.py
new file mode 100644
index 00000000..c28f9ffd
--- /dev/null
+++ b/base/base/checkpoint.py
@@ -0,0 +1,18 @@
+from datetime import datetime
+from typing import TypeAlias
+from zoneinfo import ZoneInfo
+
+from base.contest import Submission, Benchmark
+
+TIMEZONE = ZoneInfo("America/Los_Angeles")
+SPEC_VERSION = 7
+
+Uid: TypeAlias = int
+Key: TypeAlias = str
+
+Submissions: TypeAlias = dict[Key, Submission]
+Benchmarks: TypeAlias = dict[Key, Benchmark]
+
+
+def current_time() -> datetime:
+    return datetime.now(tz=TIMEZONE)
diff --git a/neuron/neuron/config.py b/base/base/config.py
similarity index 71%
rename from neuron/neuron/config.py
rename to base/base/config.py
index c2fdc9e2..82742c12 100644
--- a/neuron/neuron/config.py
+++ b/base/base/config.py
@@ -1,5 +1,5 @@
 from argparse import ArgumentParser
-from typing import Callable, Any
+from typing import Callable
 
 from fiber.constants import FINNEY_NETWORK
 
@@ -28,11 +28,7 @@ def get_config(add_args: Callable[[ArgumentParser], None] | None = None):
 
     argument_parser.add_argument("--netuid", type=int, required=True, help="Network UID")
 
-    # Deprecated arguments that won't be used
-    argument_parser.add_argument("--logging.debug", action="store_true", help="Enable debug logging", default=False)
-    argument_parser.add_argument("--logging.trace", action="store_true", help="Enable trace logging", default=False)
-
     if add_args:
         add_args(argument_parser)
 
-    return vars(argument_parser.parse_args())
+    return vars(argument_parser.parse_known_args()[0])
diff --git a/neuron/neuron/contest.py b/base/base/contest.py
similarity index 60%
rename from neuron/neuron/contest.py
rename to base/base/contest.py
index 0c4b3f06..9979ba34 100644
--- a/neuron/neuron/contest.py
+++ b/base/base/contest.py
@@ -12,6 +12,12 @@
 SIMILARITY_SCORE_THRESHOLD = 0.7
 
 
+class BenchmarkState(IntEnum):
+    NOT_STARTED = 0
+    IN_PROGRESS = 1
+    FINISHED = 2
+
+
 class MetricType(IntEnum):
     SIMILARITY_SCORE = 0
     GENERATION_TIME = 1
@@ -21,7 +27,26 @@ class MetricType(IntEnum):
     LOAD_TIME = 5
 
 
-class MetricData(BaseModel):
+class ContestId(IntEnum):
+    FLUX_NVIDIA_4090 = 0
+    SDXL_NEWDREAM_NVIDIA_4090 = 1
+
+
+class RepositoryInfo(BaseModel):
+    url: str
+    revision: str
+
+
+class Submission(BaseModel):
+    repository_info: RepositoryInfo
+    contest_id: ContestId
+    block: int
+
+    def contest(self) -> "Contest":
+        return find_contest(self.contest_id)
+
+
+class Metrics(BaseModel):
     generation_time: float
     size: int
     vram_used: float
@@ -29,37 +54,27 @@ class MetricData(BaseModel):
     load_time: float
 
 
-class CheckpointBenchmark(BaseModel):
-    model: MetricData
+class Benchmark(BaseModel):
+    metrics: Metrics
     average_similarity: float
     min_similarity: float
 
 
-class ModelRepositoryInfo(BaseModel):
-    url: str
-    revision: str
-
-
-class ContestId(IntEnum):
-    FLUX_NVIDIA_4090 = 0
-    SDXL_NEWDREAM_NVIDIA_4090 = 1
-
-
 @dataclass
 class Contest:
     id: ContestId
     device: Device
     output_comparator: Callable[[], OutputComparator]
-    baseline_repository: ModelRepositoryInfo
+    baseline_repository: RepositoryInfo
     metric_weights: dict[MetricType, int]
 
     def __init__(
-            self,
-            contest_id: ContestId,
-            device: Device,
-            output_comparator: Callable[[], OutputComparator],
-            baseline_repository: ModelRepositoryInfo,
-            metric_weights: dict[MetricType, int]
+        self,
+        contest_id: ContestId,
+        device: Device,
+        output_comparator: Callable[[], OutputComparator],
+        baseline_repository: RepositoryInfo,
+        metric_weights: dict[MetricType, int]
     ):
         self.id = contest_id
         self.device = device
@@ -67,7 +82,7 @@ def __init__(
         self.baseline_repository = baseline_repository
         self.metric_weights = metric_weights
 
-    def calculate_score(self, baseline: MetricData, benchmark: CheckpointBenchmark) -> float:
+    def calculate_score(self, baseline: Metrics, benchmark: Benchmark) -> float:
         if benchmark.min_similarity < SIMILARITY_SCORE_THRESHOLD:
             return 0.0
 
@@ -83,22 +98,24 @@ def normalize(baseline_value: float, benchmark_value: float, metric_type: Metric
             return (relative_improvement * self.metric_weights.get(metric_type, 0)) / total_weight
 
         score = sum([
-            normalize(baseline.generation_time, benchmark.model.generation_time, MetricType.GENERATION_TIME),
-            normalize(baseline.size, benchmark.model.size, MetricType.SIZE),
-            normalize(baseline.vram_used, benchmark.model.vram_used, MetricType.VRAM_USED),
-            normalize(baseline.watts_used, benchmark.model.watts_used, MetricType.WATTS_USED),
-            normalize(baseline.load_time, benchmark.model.load_time, MetricType.LOAD_TIME)
+            normalize(baseline.generation_time, benchmark.metrics.generation_time, MetricType.GENERATION_TIME),
+            normalize(baseline.size, benchmark.metrics.size, MetricType.SIZE),
+            normalize(baseline.vram_used, benchmark.metrics.vram_used, MetricType.VRAM_USED),
+            normalize(baseline.watts_used, benchmark.metrics.watts_used, MetricType.WATTS_USED),
+            normalize(baseline.load_time, benchmark.metrics.load_time, MetricType.LOAD_TIME)
         ])
 
         return score * similarity * self.metric_weights.get(MetricType.SIMILARITY_SCORE, 0) / total_weight
 
 
+CUDA_4090_DEVICE = CudaDevice(gpu=Gpu.NVIDIA_RTX_4090)
+
 CONTESTS = [
     Contest(
         contest_id=ContestId.FLUX_NVIDIA_4090,
-        device=CudaDevice(gpu=Gpu.NVIDIA_RTX_4090),
-        output_comparator=partial(ImageOutputComparator, "cuda"),
-        baseline_repository=ModelRepositoryInfo(url="https://github.com/womboai/flux-schnell-edge-inference", revision="fbfb8f0"),
+        device=CUDA_4090_DEVICE,
+        output_comparator=partial(ImageOutputComparator, CUDA_4090_DEVICE),
+        baseline_repository=RepositoryInfo(url="https://github.com/womboai/flux-schnell-edge-inference", revision="fbfb8f0"),
         metric_weights={
             MetricType.SIMILARITY_SCORE: 3,
             MetricType.VRAM_USED: 3,
@@ -107,9 +124,9 @@ def normalize(baseline_value: float, benchmark_value: float, metric_type: Metric
     ),
     Contest(
         contest_id=ContestId.SDXL_NEWDREAM_NVIDIA_4090,
-        device=CudaDevice(gpu=Gpu.NVIDIA_RTX_4090),
-        output_comparator=partial(ImageOutputComparator, "cuda"),
-        baseline_repository=ModelRepositoryInfo(url="https://github.com/womboai/sdxl-newdream-20-inference", revision="1b3f9ea"),
+        device=CUDA_4090_DEVICE,
+        output_comparator=partial(ImageOutputComparator, CUDA_4090_DEVICE),
+        baseline_repository=RepositoryInfo(url="https://github.com/womboai/sdxl-newdream-20-inference", revision="1b3f9ea"),
         metric_weights={
             MetricType.SIMILARITY_SCORE: 1,
             MetricType.GENERATION_TIME: 1,
@@ -132,5 +149,6 @@ def find_compatible_contests() -> list[ContestId]:
     return [contest.id for contest in CONTESTS if contest.device.is_compatible()]
 
 
-CURRENT_CONTEST: Contest = find_contest(ContestId.FLUX_NVIDIA_4090)
-ACTIVE_CONTESTS = { ContestId.FLUX_NVIDIA_4090 }
+ACTIVE_CONTESTS = [
+    ContestId.FLUX_NVIDIA_4090
+]
diff --git a/neuron/neuron/device.py b/base/base/device.py
similarity index 80%
rename from neuron/neuron/device.py
rename to base/base/device.py
index 85191d68..1fbda5c9 100644
--- a/neuron/neuron/device.py
+++ b/base/base/device.py
@@ -7,6 +7,10 @@ class Gpu(Enum):
 
 
 class Device(ABC):
+    @abstractmethod
+    def get_name(self):
+        ...
+
     @abstractmethod
     def get_vram_used(self):
         ...
@@ -16,11 +20,11 @@ def get_joules(self):
         ...
 
     @abstractmethod
-    def is_compatible(self):
+    def empty_cache(self):
         ...
 
     @abstractmethod
-    def validate(self):
+    def is_compatible(self):
         ...
 
 
@@ -30,6 +34,9 @@ class CudaDevice(Device):
     def __init__(self, gpu: Gpu):
         self._gpu = gpu
 
+    def get_name(self):
+        return "cuda"
+
     def get_vram_used(self):
         import pynvml
         import torch
@@ -50,23 +57,24 @@ def get_joules(self):
         pynvml.nvmlShutdown()
         return mj / 1000.0  # convert mJ to J
 
-    def is_compatible(self):
+    def empty_cache(self):
         import torch
 
-        device_name = torch.cuda.get_device_name()
+        torch.cuda.synchronize()
+        torch.cuda.empty_cache()
 
-        return device_name == self._gpu.value
-
-    def validate(self):
+    def is_compatible(self):
         import torch
 
         device_name = torch.cuda.get_device_name()
 
-        if not self.is_compatible():
-            raise ContestDeviceValidationError(f"Incompatible device {device_name} when {self._gpu.name} is required.")
+        return device_name == self._gpu.value
 
 
 class MpsDevice(Device):
+    def get_name(self):
+        return "mps"
+
     def get_vram_used(self):
         import torch
 
@@ -75,15 +83,17 @@ def get_vram_used(self):
     def get_joules(self):
         return 0  # TODO
 
+    def empty_cache(self):
+        import torch
+
+        torch.mps.synchronize()
+        torch.mps.empty_cache()
+
     def is_compatible(self):
         import torch
 
         return torch.backends.mps.is_available()
 
-    def validate(self):
-        if not self.is_compatible():
-            raise ContestDeviceValidationError("MPS is not available but is required.")
-
 
 class ContestDeviceValidationError(Exception):
     def __init__(self, message: str):
diff --git a/neuron/neuron/random_inputs.py b/base/base/inputs_api.py
similarity index 56%
rename from neuron/neuron/random_inputs.py
rename to base/base/inputs_api.py
index 28baaad0..4959f4d0 100644
--- a/neuron/neuron/random_inputs.py
+++ b/base/base/inputs_api.py
@@ -1,12 +1,10 @@
 import os
-from zoneinfo import ZoneInfo
 
 import requests
 from pydantic import RootModel
 
 from pipelines import TextToImageRequest
 
-TIMEZONE = ZoneInfo("America/Los_Angeles")
 INPUTS_ENDPOINT = os.getenv("INPUTS_ENDPOINT", "https://edge-inputs.api.wombo.ai")
 
 
@@ -20,3 +18,18 @@ def random_inputs() -> list[TextToImageRequest]:
     response.raise_for_status()
 
     return RootModel[list[TextToImageRequest]].model_validate_json(response.text).root
+
+
+def blacklisted_keys() -> dict:
+    response = requests.get(
+        f"{INPUTS_ENDPOINT}/blacklist", headers={
+            "Content-Type": "application/json"
+        },
+    )
+
+    response.raise_for_status()
+    return response.json()
+
+
+def is_blacklisted(blacklist: dict, hotkey: str, coldkey: str):
+    return hotkey in blacklist["hotkeys"] or coldkey in blacklist["coldkeys"]
diff --git a/neuron/neuron/network_commitments.py b/base/base/network_commitments.py
similarity index 99%
rename from neuron/neuron/network_commitments.py
rename to base/base/network_commitments.py
index 692e1eee..d5dbe80d 100644
--- a/neuron/neuron/network_commitments.py
+++ b/base/base/network_commitments.py
@@ -1,6 +1,5 @@
 from struct import pack, unpack
 
-
 _UINT_16_SIZE = 2
 _UINT_32_SIZE = 4
 
diff --git a/neuron/neuron/output_comparator.py b/base/base/output_comparator.py
similarity index 85%
rename from neuron/neuron/output_comparator.py
rename to base/base/output_comparator.py
index 6823229e..7f0badb2 100644
--- a/neuron/neuron/output_comparator.py
+++ b/base/base/output_comparator.py
@@ -1,8 +1,11 @@
+import gc
 from abc import ABC, abstractmethod
 from io import BytesIO
 from typing import ContextManager
 
-from transformers import CLIPProcessor, CLIPVisionModelWithProjection
+from transformers import CLIPProcessor, CLIPVisionModelWithProjection, PreTrainedModel
+
+from base.device import Device
 
 
 class OutputComparator(ContextManager, ABC):
@@ -17,9 +20,13 @@ def __wrapped_compare(self, baseline: bytes, optimized: bytes):
 
 
 class ImageOutputComparator(OutputComparator):
-    def __init__(self, device: str):
+    device: Device
+    clip: PreTrainedModel
+    processor: CLIPProcessor
+
+    def __init__(self, device: Device):
         self.device = device
-        self.clip = CLIPVisionModelWithProjection.from_pretrained("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k").to(self.device)
+        self.clip = CLIPVisionModelWithProjection.from_pretrained("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k").to(device.get_name())
         self.processor = CLIPProcessor.from_pretrained("laion/CLIP-ViT-bigG-14-laion2B-39B-b160k")
 
     def compare(self, baseline: bytes, optimized: bytes):
@@ -40,9 +47,9 @@ def load_image(data: bytes):
                 return numpy.array(Image.open(fp).convert("RGB"))
 
         def clip_embeddings(image: numpy.ndarray):
-            processed_input = self.processor(images=image, return_tensors="pt").to(self.device)
+            processed_input = self.processor(images=image, return_tensors="pt").to(self.device.get_name())
 
-            return self.clip(**processed_input).image_embeds.to(self.device)
+            return self.clip(**processed_input).image_embeds.to(self.device.get_name())
 
         baseline_array = load_image(baseline)
         optimized_array = load_image(optimized)
@@ -66,8 +73,8 @@ def __enter__(self):
         return self
 
     def __exit__(self, exc_type, exc_value, traceback):
-        import torch
-
         del self.clip
         del self.processor
-        getattr(torch, self.device).empty_cache()
+
+        gc.collect()
+        self.device.empty_cache()
diff --git a/base/base/submissions.py b/base/base/submissions.py
new file mode 100644
index 00000000..57e58f61
--- /dev/null
+++ b/base/base/submissions.py
@@ -0,0 +1,167 @@
+from typing import Annotated
+
+from fiber.chain.commitments import publish_raw_commitment, _deserialize_commitment_field
+from fiber.chain.metagraph import Metagraph
+from fiber.logging_utils import get_logger
+from pydantic import BaseModel, Field
+from substrateinterface import SubstrateInterface, Keypair
+from substrateinterface.storage import StorageKey
+
+from .checkpoint import SPEC_VERSION, Submissions, Key
+from .contest import RepositoryInfo, find_contest, Submission, ContestId, ACTIVE_CONTESTS
+from .inputs_api import is_blacklisted, blacklisted_keys
+from .network_commitments import Encoder, Decoder
+
+logger = get_logger(__name__)
+
+REVISION_LENGTH = 7
+
+
+class CheckpointSubmission(BaseModel):
+    repository: str
+    revision: Annotated[str, Field(min_length=REVISION_LENGTH, max_length=REVISION_LENGTH)]
+    contest_id: ContestId
+
+    def encode(self, encoder: Encoder):
+        repository = self.repository.replace("https://", "")
+        parts = repository.split("/")
+        provider = parts[0]
+        owner = parts[1]
+        repository_name = parts[2]
+
+        encoder.write_str(provider)
+        encoder.write_str(f"{owner}/{repository_name}")
+        encoder.write_sized_str(self.revision)
+        encoder.write_uint16(self.contest_id.value)
+
+    @classmethod
+    def decode(cls, decoder: Decoder):
+        provider = decoder.read_str()
+        repository = decoder.read_str()
+        revision = decoder.read_sized_str(REVISION_LENGTH)
+        contest_id = ContestId(decoder.read_uint16())
+
+        return cls(
+            repository=f"https://{provider}/{repository}",
+            revision=revision,
+            contest_id=contest_id,
+        )
+
+
+def make_submission(
+    substrate: SubstrateInterface,
+    netuid: int,
+    keypair: Keypair,
+    submissions: list[CheckpointSubmission],
+):
+    encoder = Encoder()
+
+    encoder.write_uint16(SPEC_VERSION)
+
+    for submission in submissions:
+        submission.encode(encoder)
+
+    data = encoder.finish()
+
+    publish_raw_commitment(
+        substrate,
+        keypair,
+        netuid,
+        data,
+        wait_for_finalization=False,
+    )
+
+
+def get_submissions(
+    substrate: SubstrateInterface,
+    metagraph: Metagraph,
+    block: int
+) -> Submissions:
+    submissions: Submissions = {}
+    storage_keys: list[StorageKey] = []
+
+    blacklist = blacklisted_keys()
+    hotkeys = [hotkey for hotkey, node in metagraph.nodes.items() if not is_blacklisted(blacklist, hotkey, node.coldkey)]
+    for hotkey in hotkeys:
+        storage_keys.append(substrate.create_storage_key(
+            "Commitments",
+            "CommitmentOf",
+            [metagraph.netuid, hotkey]
+        ))
+
+    commitments = substrate.query_multi(
+        storage_keys=storage_keys,
+        block_hash=substrate.get_block_hash(block),
+    )
+
+    for storage, commitment in commitments:
+        hotkey = storage.params[1]
+        try:
+            if not commitment or not commitment.value:
+                continue
+
+            fields = commitment.value["info"]["fields"]
+            if not fields:
+                continue
+
+            field = _deserialize_commitment_field(fields[0])
+            if field is None:
+                continue
+
+            decoder = Decoder(field[1])
+            spec_version = decoder.read_uint16()
+            if spec_version != SPEC_VERSION:
+                continue
+
+            while not decoder.eof:
+                info = CheckpointSubmission.decode(decoder)
+
+                if info.contest_id not in ACTIVE_CONTESTS:
+                    continue
+
+                if info.repository == find_contest(info.contest_id).baseline_repository.url:
+                    continue
+
+                repository_info = RepositoryInfo(url=info.repository, revision=info.revision)
+                submitted_block = int(commitment.value["block"])
+                submissions[hotkey] = Submission(
+                    repository_info=repository_info,
+                    contest_id=info.contest_id,
+                    block=submitted_block
+                )
+        except Exception as e:
+            logger.error(f"Failed to get submission from miner {hotkey}: {e}")
+            continue
+
+    return deduplicate_submissions(submissions)
+
+
+def deduplicate_submissions(submissions: Submissions) -> Submissions:
+    existing_repositories: dict[str, tuple[Key, Submission]] = {}
+    existing_revisions: dict[str, tuple[Key, Submission]] = {}
+    to_remove: set[Key] = set()
+
+    for key, submission in submissions.items():
+        url = submission.repository_info.url
+        revision = submission.repository_info.revision
+        block = submission.block
+
+        existing_repository_key, existing_repository = existing_repositories.get(url, (None, None))
+        existing_revision_key, existing_revision = existing_revisions.get(revision, (None, None))
+
+        if (existing_repository and existing_repository.block < block) or (existing_revision and existing_revision.block < block):
+            to_remove.add(key)
+            continue
+
+        if existing_repository:
+            to_remove.add(existing_repository_key)
+        if existing_revision:
+            to_remove.add(existing_revision_key)
+
+        existing_repositories[url] = key, submission
+        existing_revisions[revision] = key, submission
+
+    for key in to_remove:
+        submissions.pop(key)
+        logger.info(f"Skipping duplicate submission: {key}")
+    return submissions
diff --git a/neuron/pyproject.toml b/base/pyproject.toml
similarity index 54%
rename from neuron/pyproject.toml
rename to base/pyproject.toml
index 6479c34b..1a38c224 100644
--- a/neuron/pyproject.toml
+++ b/base/pyproject.toml
@@ -3,26 +3,21 @@ requires = ["setuptools >= 75.0"]
 build-backend = "setuptools.build_meta"
 
 [project]
-name = "edge-maxxing-neuron"
+name = "edge-maxxing-base"
 description = "The base neuron which validators & miners inherent from"
 requires-python = ">=3.10,<3.13"
 version = "1.0.0"
 dependencies = [
-    "fiber @ git+https://github.com/womboai/fiber@weights",
-    "GitPython==3.1.43",
-    "torch==2.5.1",
-    "pynvml==11.5.3",
-    "diffusers==0.31.0",
-    "transformers==4.46.2",
-    "accelerate==1.1.0",
-    "omegaconf==2.3.0",
-    "torchvision==0.20.1",
-    "scikit-image==0.24.0",
-    "opencv-python==4.10.0.84",
-    "ImageHash==4.3.1",
-    "toml==0.10.2",
-    "opentelemetry-instrumentation>=0.49b2",
     "edge-maxxing-pipelines==1.0.0",
+    "fiber @ git+https://github.com/rayonlabs/fiber.git@1.0.0#egg=fiber[chain]",
+    "opentelemetry-instrumentation>=0.49b2",
+    "transformers>=4.46.3",
+    "diffusers>=0.31.0",
+    "accelerate>=1.1.1",
+    "pynvml>=11.5.3",
+    "scikit-image>=0.24.0",
+    "opencv-python>=4.10.0.84",
+    "gitpython>=3.1.43",
 ]
 
 [tool.uv.sources]
@@ -34,9 +29,13 @@ dev = [
 ]
 
 [tool.pytype]
-inputs = ["neuron"]
+inputs = [
+    "base",
+    "testing",
+]
 
 [tool.setuptools]
 packages = [
-    "neuron",
+    "base",
+    "testing",
 ]
diff --git a/base/testing/__init__.py b/base/testing/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/base/testing/benchmarker.py b/base/testing/benchmarker.py
new file mode 100644
index 00000000..c75b7103
--- /dev/null
+++ b/base/testing/benchmarker.py
@@ -0,0 +1,169 @@
+from concurrent.futures import CancelledError
+from datetime import timedelta
+from pathlib import Path
+from random import choice
+from statistics import mean
+from threading import Event, Thread
+from time import perf_counter
+
+from fiber.logging_utils import get_logger
+from opentelemetry import trace
+
+from base.checkpoint import Key, Benchmarks
+from base.contest import Contest, RepositoryInfo, Benchmark, BenchmarkState
+from base.inputs_api import random_inputs
+from pipelines import TextToImageRequest
+from .inference_sandbox import BenchmarkOutput, InferenceSandbox
+
+logger = get_logger(__name__)
+tracer = trace.get_tracer(__name__)
+
+
+class Benchmarker:
+    _thread: Thread | None = None
+    _stop_flag: Event = Event()
+
+    _sandbox_directory: Path
+    _sandbox_args: list[str]
+
+    start_timestamp: float = 0
+    state: BenchmarkState = BenchmarkState.NOT_STARTED
+    benchmarks: Benchmarks = {}
+    invalid_submissions: set[Key] = set()
+    baseline: BenchmarkOutput | None = None
+    submission_times: list[float] = []
+
+    def __init__(self, sandbox_directory: Path, sandbox_args: list[str]):
+        self._sandbox_directory = sandbox_directory
+        self._sandbox_args = sandbox_args
+
+    @tracer.start_as_current_span("compare")
+    def compare(
+        self,
+        contest: Contest,
+        benchmark_output: BenchmarkOutput,
+        stop_flag: Event,
+    ) -> Benchmark:
+        similarities: list[float] = []
+        with contest.output_comparator() as comparator:
+            for baseline_output, optimized_output in zip(self.baseline.outputs, benchmark_output.outputs):
+                if stop_flag.is_set():
+                    raise CancelledError()
+
+                similarities.append(comparator(baseline_output, optimized_output))
+
+        average_similarity = mean(similarities)
+        min_similarity = min(similarities)
+
+        return Benchmark(
+            metrics=benchmark_output.metrics,
+            average_similarity=average_similarity,
+            min_similarity=min_similarity,
+        )
+
+    def _is_done(self, submissions: dict[Key, RepositoryInfo]) -> bool:
+        return len(self.benchmarks) + len(self.invalid_submissions) == len(submissions)
+
+    @tracer.start_as_current_span("benchmark")
+    def _benchmark_submission(
+        self,
+        contest: Contest,
+        inputs: list[TextToImageRequest],
+        repository_info: RepositoryInfo
+    ) -> BenchmarkOutput:
+        return InferenceSandbox(
+            sandbox_args=self._sandbox_args,
+            sandbox_directory=self._sandbox_directory,
+            contest=contest,
+            repository_info=repository_info,
+            inputs=inputs,
+            stop_flag=self._stop_flag,
+        ).benchmark()
+
+    @tracer.start_as_current_span("benchmark_baseline")
+    def _benchmark_baseline(self, contest: Contest, inputs: list[TextToImageRequest]):
+        logger.info("Benchmarking baseline")
+        while not self.baseline and not self._stop_flag.is_set():
+            try:
+                self.baseline = self._benchmark_submission(contest, inputs, contest.baseline_repository)
+            except CancelledError:
+                logger.warning("Benchmarking was canceled while testing the baseline")
+                return
+            except Exception as e:
+                logger.error("Failed to generate baseline samples, retrying in 10 minutes", exc_info=e)
+                self._stop_flag.wait(600)
+
+    def benchmark_submissions(self, contest: Contest, submissions: dict[Key, RepositoryInfo]):
+        self.state = BenchmarkState.IN_PROGRESS
+        self.benchmarks.clear()
+        self.invalid_submissions.clear()
+        self.baseline = None
+        self.submission_times.clear()
+
+        inputs = random_inputs()
+        self._benchmark_baseline(contest, inputs)
+
+        logger.info(f"Benchmarking {len(submissions)} submissions")
+        while not self._is_done(submissions) and self.baseline and not self._stop_flag.is_set():
+            start_time = perf_counter()
+            key = choice(list(submissions.keys() - self.benchmarks.keys()))
+            submission = submissions[key]
+            logger.info(f"Benchmarking submission '{submission.url}' with revision '{submission.revision}'")
+            try:
+                benchmark_output = self._benchmark_submission(contest, inputs, submission)
+                benchmark = self.compare(contest, benchmark_output, self._stop_flag)
+                self.benchmarks[key] = benchmark
+            except CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"Failed to benchmark submission '{submission}': '{e}'", exc_info=e)
+                self.invalid_submissions.add(key)
+            finally:
+                self.submission_times.append(perf_counter() - start_time)
+
+            average_benchmarking_time = self.get_average_benchmarking_time()
+            if average_benchmarking_time:
+                benchmarked = len(self.benchmarks) + len(self.invalid_submissions)
+                eta = (len(submissions) - benchmarked) * average_benchmarking_time
+                logger.info(f"{benchmarked}/{len(submissions)} benchmarked. Average benchmark time: {average_benchmarking_time:.2f}s, ETA: {timedelta(seconds=int(eta))}")
+
+        if self._is_done(submissions):
+            logger.info("Benchmarking complete")
+            self.state = BenchmarkState.FINISHED
+        else:
+            logger.warning("Benchmarking canceled")
+            self.state = BenchmarkState.NOT_STARTED
+
+    def get_average_benchmarking_time(self) -> float | None:
+        return (
+            sum(self.submission_times) / len(self.submission_times)
+            if self.submission_times
+            else None
+        )
+
+    def shutdown(self):
+        if self._thread and self._thread.is_alive():
+            logger.info("Attempting to cancel previous benchmarking")
+            self._stop_flag.set()
+            self._thread.join(timeout=60)
+            if self._thread.is_alive():
+                logger.warning("Benchmarking was not stopped gracefully.")
+            else:
+                logger.info("Benchmarking was stopped gracefully.")
+
+    def start_benchmarking(self, contest: Contest, submissions: dict[Key, RepositoryInfo]):
+        if not submissions:
+            logger.warning("No submissions to benchmark")
+            return
+
+        logger.info(f"Started benchmarking for {len(submissions)} submissions")
+
+        self.shutdown()
+
+        self._stop_flag.clear()
+        self._thread = Thread(
+            target=self.benchmark_submissions,
+            args=(contest, submissions,),
+            daemon=True,
+        )
+        self._thread.start()
diff --git a/neuron/neuron/submission_tester/blacklist.sh b/base/testing/blacklist.sh
similarity index 78%
rename from neuron/neuron/submission_tester/blacklist.sh
rename to base/testing/blacklist.sh
index 011ae26e..e7f936c6 100755
--- a/neuron/neuron/submission_tester/blacklist.sh
+++ b/base/testing/blacklist.sh
@@ -2,10 +2,8 @@
 
 set -e
 
-BLACKLISTED_DEPENDENCIES=$1
-
 find . -type f -not -path '*/\.git/*' -not -path '*/.venv/*' -not -path '*/models/*' -print0 | while IFS= read -r -d '' file; do
-  for dependency in $BLACKLISTED_DEPENDENCIES; do
+  for dependency in "$@"; do
      if [[ "$file" == *"$dependency"* ]]; then
        echo "Found blacklisted dependency '$dependency' in filename '$file'"
        exit 1
@@ -13,11 +11,11 @@ find . -type f -not -path '*/\.git/*' -not -path '*/.venv/*' -not -path '*/model
   done
 
   while IFS= read -r line; do
-    for dependency in $BLACKLISTED_DEPENDENCIES; do
+    for dependency in "$@"; do
       if [[ "$line" == *"$dependency"* ]]; then
         echo "Found blacklisted dependency '$dependency' in file '$file'"
         exit 1
       fi
     done
   done < "$file"
-done
\ No newline at end of file
+done
diff --git a/base/testing/clear_cache.sh b/base/testing/clear_cache.sh
new file mode 100755
index 00000000..0c7974c3
--- /dev/null
+++ b/base/testing/clear_cache.sh
@@ -0,0 +1,9 @@
+#!/bin/bash
+
+set -e
+
+cd ~/.cache
+
+find huggingface -mindepth 1 -delete || true
+find pip -mindepth 1 -delete || true
+find uv -mindepth 1 -delete || true
diff --git a/neuron/neuron/submission_tester/clone.sh b/base/testing/clone.sh
similarity index 100%
rename from neuron/neuron/submission_tester/clone.sh
rename to base/testing/clone.sh
diff --git a/neuron/neuron/submission_tester/download_huggingface_models.sh b/base/testing/download_huggingface_models.sh
similarity index 76%
rename from neuron/neuron/submission_tester/download_huggingface_models.sh
rename to base/testing/download_huggingface_models.sh
index b8d4c2c5..291067b0 100755
--- a/neuron/neuron/submission_tester/download_huggingface_models.sh
+++ b/base/testing/download_huggingface_models.sh
@@ -2,9 +2,7 @@
 
 set -e
 
-MODELS=$1
-
-for model in $MODELS
+for model in "$@"
 do
     HF_HUB_ENABLE_HF_TRANSFER=1 ~/.local/bin/huggingface-cli download "$model"
 done
\ No newline at end of file
diff --git a/base/testing/inference_sandbox.py b/base/testing/inference_sandbox.py
new file mode 100644
index 00000000..1c87ee31
--- /dev/null
+++ b/base/testing/inference_sandbox.py
@@ -0,0 +1,264 @@
+import shutil
+from concurrent.futures import CancelledError
+from multiprocessing.connection import Client
+from os.path import abspath
+from pathlib import Path
+from subprocess import run, Popen, PIPE
+from threading import Event
+from time import perf_counter
+
+import toml
+from fiber.logging_utils import get_logger
+from huggingface_hub import HfApi
+from opentelemetry import trace
+from pydantic import BaseModel
+
+from base.checkpoint import SPEC_VERSION
+from base.contest import RepositoryInfo, Contest, Metrics
+from pipelines import TextToImageRequest
+from .vram_monitor import VRamMonitor
+
+CLEAR_CACHE = abspath(Path(__file__).parent / "clear_cache.sh")
+CLONE = abspath(Path(__file__).parent / "clone.sh")
+BLACKLIST = abspath(Path(__file__).parent / "blacklist.sh")
+SYNC_UV = abspath(Path(__file__).parent / "sync_uv.sh")
+DOWNLOAD_HUGGINGFACE_MODELS = abspath(Path(__file__).parent / "download_huggingface_models.sh")
+
+NETWORK_JAIL = abspath(Path(__file__).parent / "libnetwork_jail.so")
+START_INFERENCE_SCRIPT = abspath(Path(__file__).parent / "start_inference.sh")
+
+STORAGE_THRESHOLD_GB = 50
+MAX_HF_MODEL_SIZE_GB = 100
+MAX_REPO_SIZE_MB = 16
+
+LOAD_TIMEOUT = 240
+
+BLACKLISTED_DEPENDENCIES = [
+    "pyarmor"
+]
+
+logger = get_logger(__name__)
+tracer = trace.get_tracer(__name__)
+hf_api = HfApi()
+
+
+class InvalidSubmissionError(Exception):
+    ...
+
+
+class BenchmarkOutput(BaseModel):
+    metrics: Metrics
+    outputs: list[bytes]
+
+
+class InferenceSandbox:
+    _sandbox_args: list[str]
+    _sandbox_directory: Path
+    _contest: Contest
+    _repository_info: RepositoryInfo
+    _inputs: list[TextToImageRequest]
+    _stop_flag: Event
+    _socket_path: Path
+
+    def __init__(
+        self,
+        sandbox_args: list[str],
+        sandbox_directory: Path,
+        contest: Contest,
+        repository_info: RepositoryInfo,
+        inputs: list[TextToImageRequest],
+        stop_flag: Event,
+    ):
+        self._sandbox_args = sandbox_args
+        self._sandbox_directory = sandbox_directory
+        self._contest = contest
+        self._repository_info = repository_info
+        self._inputs = inputs
+        self._stop_flag = stop_flag
+        self._socket_path = self._sandbox_directory / "inferences.sock"
+
+    def _run(self, script: str, args: list[str]):
+        if self._stop_flag.is_set():
+            raise CancelledError()
+
+        process = run(
+            [
+                *self._sandbox_args,
+                script,
+                *args,
+            ],
+            capture_output=True,
+            encoding='utf-8',
+            cwd=self._sandbox_directory.absolute(),
+        )
+        if process.stdout.strip():
+            logger.info(process.stdout)
+        if process.stderr.strip():
+            logger.info(process.stderr)
+        if process.returncode:
+            raise InvalidSubmissionError(f"Failed to run {script}")
+
+    @tracer.start_as_current_span("check_space")
+    def _check_space(self):
+        free_space = shutil.disk_usage("/").free
+        if free_space < STORAGE_THRESHOLD_GB * 1024 ** 3:
+            self._run(CLEAR_CACHE, [])
+            new_free_space = shutil.disk_usage("/").free
+            logger.info(f"Cleared {(new_free_space - free_space) / 1024 ** 3:.2f} GB of caches")
+
+    @tracer.start_as_current_span("clone_repository")
+    def _clone(self) -> int:
+        self._run(CLONE, [self._repository_info.url, self._repository_info.revision])
+
+        repo_size = sum(
+            file.stat().st_size for file in self._sandbox_directory.rglob("*")
+            if ".git" not in file.parts and ".venv" not in file.parts
+        )
+        if repo_size > MAX_REPO_SIZE_MB * 1024 ** 2:
+            raise InvalidSubmissionError(f"Size of repository exceeds {MAX_REPO_SIZE_MB} MB")
+
+        return repo_size
+
+    @tracer.start_as_current_span("check_blacklist")
+    def _check_blacklist(self):
+        self._run(BLACKLIST, BLACKLISTED_DEPENDENCIES)
+
+    @tracer.start_as_current_span("sync_uv")
+    def _sync_uv(self):
+        self._run(SYNC_UV, [])
+
+    @tracer.start_as_current_span("download_huggingface_models")
+    def _download_huggingface_models(self, models: list[str]) -> int:
+        try:
+            total_model_size = 0
+            for model in models:
+                model_info = hf_api.model_info(repo_id=model, files_metadata=True)
+                for sibling in model_info.siblings:
+                    total_model_size += sibling.size
+        except Exception as e:
+            raise InvalidSubmissionError("Failed to get model info") from e
+
+        if total_model_size > MAX_HF_MODEL_SIZE_GB * 1024 ** 3:
+            raise InvalidSubmissionError(f"Size of all Hugging Face models exceeds {MAX_HF_MODEL_SIZE_GB} GB")
+
+        self._run(DOWNLOAD_HUGGINGFACE_MODELS, models)
+
+        return total_model_size
+
+    @tracer.start_as_current_span("setup")
+    def _setup_sandbox(self) -> int:
+        self._check_space()
+        repository_size = self._clone()
+
+        try:
+            with open(self._sandbox_directory / "pyproject.toml", 'r') as file:
+                pyproject = toml.load(file)
+                version = int(pyproject["project"]["version"])
+                models = pyproject["tool"]["edge-maxxing"]["models"]
+        except Exception as e:
+            raise InvalidSubmissionError("Failed to read submission info") from e
+
+        if version != SPEC_VERSION:
+            raise InvalidSubmissionError(f"Submission is at version {version} while expected version is {SPEC_VERSION}")
+
+        self._check_blacklist()
+        self._sync_uv()
+        huggingface_models_size = self._download_huggingface_models(models)
+
+        return repository_size + huggingface_models_size
+
+    @tracer.start_as_current_span("wait_for_socket")
+    def wait_for_socket(self, process: Popen) -> float:
+        start = perf_counter()
+        for _ in range(LOAD_TIMEOUT):
+            if self._socket_path.exists():
+                break
+            self._stop_flag.wait(1)
+            check_process(process)
+            if self._stop_flag.is_set():
+                raise CancelledError()
+        else:
+            raise InvalidSubmissionError(f"Timed out after {LOAD_TIMEOUT} seconds")
+        return perf_counter() - start
+
+    @tracer.start_as_current_span("start_inference")
+    def benchmark(self) -> BenchmarkOutput:
+        size = self._setup_sandbox()
+        start_vram = self._contest.device.get_vram_used()
+
+        metrics: list[Metrics] = []
+        outputs: list[bytes] = []
+
+        logger.info("Loading pipeline")
+        with Popen(
+            [
+                *self._sandbox_args,
+                START_INFERENCE_SCRIPT,
+                NETWORK_JAIL
+            ],
+            cwd=self._sandbox_directory,
+            stdout=PIPE,
+            stderr=PIPE,
+            text=True,
+            bufsize=1,
+        ) as process:
+            try:
+                load_time = self.wait_for_socket(process)
+                with Client(abspath(self._socket_path)) as client:
+                    logger.info(f"Benchmarking {len(self._inputs)} samples")
+                    for i, request in enumerate(self._inputs):
+                        logger.info(f"Sample {i + 1}/{len(self._inputs)}")
+                        start_joules = self._contest.device.get_joules()
+                        vram_monitor = VRamMonitor(self._contest)
+
+                        data = request.model_dump_json().encode("utf-8")
+                        logger.debug(data)
+                        client.send_bytes(data)
+
+                        start = perf_counter()
+                        output = client.recv_bytes()
+
+                        generation_time = perf_counter() - start
+                        joules_used = self._contest.device.get_joules() - start_joules
+                        watts_used = joules_used / generation_time
+                        vram_used = vram_monitor.complete()
+
+                        metrics.append(Metrics(
+                            generation_time=generation_time,
+                            size=size,
+                            vram_used=vram_used,
+                            watts_used=watts_used,
+                            load_time=load_time,
+                        ))
+                        outputs.append(output)
+                        check_process(process)
+            finally:
+                log_process(process)
+
+        average_generation_time = sum(metric.generation_time for metric in metrics) / len(metrics)
+        vram_used = max(metric.vram_used for metric in metrics) - start_vram
+        watts_used = max(metric.watts_used for metric in metrics)
+        return BenchmarkOutput(
+            metrics=Metrics(
+                generation_time=average_generation_time,
+                size=size,
+                vram_used=vram_used,
+                watts_used=watts_used,
+                load_time=load_time,
+            ),
+            outputs=outputs,
+        )
+
+
+def check_process(process: Popen):
+    if process.poll():
+        raise InvalidSubmissionError(f"Inference crashed with exit code {process.returncode}")
+
+
+def log_process(process: Popen):
+    stdout = process.stdout.read()
+    stderr = process.stderr.read()
+    if stdout:
+        logger.info(stdout)
+    if stderr:
+        logger.info(stderr)
diff --git a/neuron/neuron/submission_tester/libnetwork_jail.so b/base/testing/libnetwork_jail.so
similarity index 100%
rename from neuron/neuron/submission_tester/libnetwork_jail.so
rename to base/testing/libnetwork_jail.so
diff --git a/neuron/neuron/submission_tester/start_inference.sh b/base/testing/start_inference.sh
similarity index 100%
rename from neuron/neuron/submission_tester/start_inference.sh
rename to base/testing/start_inference.sh
diff --git a/base/testing/sync_uv.sh b/base/testing/sync_uv.sh
new file mode 100755
index 00000000..e96f3b75
--- /dev/null
+++ b/base/testing/sync_uv.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+
+set -e
+
+~/.local/bin/uv sync
diff --git a/neuron/neuron/submission_tester/vram_monitor.py b/base/testing/vram_monitor.py
similarity index 87%
rename from neuron/neuron/submission_tester/vram_monitor.py
rename to base/testing/vram_monitor.py
index 094ecb88..c17ccd53 100644
--- a/neuron/neuron/submission_tester/vram_monitor.py
+++ b/base/testing/vram_monitor.py
@@ -1,10 +1,10 @@
 from threading import Thread, Event
-from time import sleep
 
-from .. import Contest
+from base.contest import Contest
 
 SAMPLE_RATE_MS = 10
 
+
 class VRamMonitor:
     _contest: Contest
     _thread: Thread
@@ -21,7 +21,7 @@ def __init__(self, contest: Contest):
     def _monitor(self):
         while not self._stop_flag.is_set():
             self._vram_usage = max(self._vram_usage, self._contest.device.get_vram_used())
-            sleep(SAMPLE_RATE_MS / 1000)
+            self._stop_flag.wait(SAMPLE_RATE_MS / 1000)
 
     def complete(self) -> int:
         self._stop_flag.set()
diff --git a/miner/miner/submit.py b/miner/miner/submit.py
index 74135eef..5fe4dfe4 100644
--- a/miner/miner/submit.py
+++ b/miner/miner/submit.py
@@ -1,55 +1,42 @@
-import base64
-import json
 import re
-import shutil
 from argparse import ArgumentParser
 from pathlib import Path
+from tempfile import TemporaryDirectory
 
 from fiber.chain.chain_utils import load_hotkey_keypair
 from fiber.chain.interface import get_substrate
 from fiber.logging_utils import get_logger
 from git import GitCommandError, cmd
+from substrateinterface import Keypair
 
-from neuron import (
-    CheckpointSubmission,
-    get_config,
-    find_contest,
-    Contest,
-    CURRENT_CONTEST,
-    CONTESTS,
-    ContestId,
-    REVISION_LENGTH,
-    make_submission,
-    random_inputs,
-    ModelRepositoryInfo,
-    TextToImageRequest,
-    GenerationOutput,
-    BENCHMARKS_VERSION,
-)
-from neuron.submission_tester import (
-    generate_baseline,
-    compare_checkpoints,
-    BaselineBenchmark,
-    MetricData,
-)
-
-VALID_PROVIDER_REGEX = r'^[a-zA-Z0-9-.]+$'
-VALID_REPO_REGEX = r'^[a-zA-Z0-9._-]+\/[a-zA-Z0-9._-]+$'
-VALID_REVISION_REGEX = r"^[a-f0-9]{7}$"
+from base.config import get_config
+from base.contest import Contest, find_contest, CONTESTS, ContestId, ACTIVE_CONTESTS
+from base.submissions import CheckpointSubmission, make_submission
+from testing.benchmarker import Benchmarker
 
-MODEL_DIRECTORY = Path("model")
-BASELINE_CACHE_JSON = Path("baseline_cache.json")
+VALID_REPO_REGEX = r"^https:\/\/[a-zA-Z0-9.-]+\/[a-zA-Z0-9._-]+\/[a-zA-Z0-9._-]+$"
+VALID_REVISION_REGEX = r"^[a-f0-9]{7}$"
 
 logger = get_logger(__name__)
 
 
-def add_extra_args(argument_parser: ArgumentParser):
-    argument_parser.add_argument(
-        "--provider",
-        type=str,
-        help="The git provider containing the repository",
-    )
+def start_benchmarking(contest: Contest, keypair: Keypair, submission: CheckpointSubmission):
+    if not contest.device.is_compatible():
+        logger.warning("Benchmarking on an incompatible device. Results will not be accurate.")
+
+    with TemporaryDirectory() as temp_dir:
+        benchmarker = Benchmarker(
+            sandbox_directory=Path(temp_dir),
+            sandbox_args=[]
+        )
 
+        benchmarker.benchmark_submissions(
+            contest=contest,
+            submissions={keypair.ss58_address: submission},
+        )
+
+
+def add_extra_args(argument_parser: ArgumentParser):
     argument_parser.add_argument(
         "--repository",
         type=str,
@@ -76,91 +63,7 @@ def add_extra_args(argument_parser: ArgumentParser):
     )
 
 
-def load_baseline_cache(inputs: list[TextToImageRequest]) -> BaselineBenchmark | None:
-    try:
-        if not BASELINE_CACHE_JSON.exists():
-            return None
-
-        with open(BASELINE_CACHE_JSON, "r") as f:
-            data = json.load(f)
-
-            benchmarks_version = data["benchmarks_version"]
-            if BENCHMARKS_VERSION != benchmarks_version:
-                logger.info(f"Baseline cache is outdated, regenerating baseline")
-                return None
-
-            cached_inputs = [TextToImageRequest(**input_data) for input_data in data["inputs"]]
-            if cached_inputs != inputs:
-                logger.info("Contest inputs have changed, regenerating baseline")
-                return None
-
-            metrics = MetricData(**data["metrics"])
-            outputs = [
-                GenerationOutput(
-                    output=base64.b64decode(output_data["output"]),
-                    generation_time=output_data["generation_time"],
-                    vram_used=output_data["vram_used"],
-                    watts_used=output_data["watts_used"]
-                )
-                for output_data in data["outputs"]
-            ]
-            return BaselineBenchmark(inputs=inputs, outputs=outputs, metric_data=metrics)
-    except Exception as e:
-        logger.error(f"Failed to load baseline cache: {e}. Clearing.")
-        return None
-
-
-def save_baseline_cache(baseline: BaselineBenchmark):
-    with open(BASELINE_CACHE_JSON, "w") as f:
-        data = {
-            "benchmarks_version": BENCHMARKS_VERSION,
-            "inputs": [request.model_dump(exclude_none=True) for request in baseline.inputs],
-            "outputs": [
-                {
-                    "output": base64.b64encode(output.output).decode('utf-8'),
-                    "generation_time": output.generation_time,
-                    "vram_used": output.vram_used,
-                    "watts_used": output.watts_used
-                }
-                for output in baseline.outputs
-            ],
-            "metrics": baseline.metric_data.model_dump(exclude_none=True),
-        }
-        json.dump(data, f, indent=4)
-
-
-def start_benchmarking(contest: Contest, submission: CheckpointSubmission):
-    logger.info("Generating baseline samples to compare")
-    if not MODEL_DIRECTORY.exists():
-        MODEL_DIRECTORY.mkdir()
-    inputs = random_inputs()
-
-    baseline = load_baseline_cache(inputs)
-    if baseline is None:
-        baseline = generate_baseline(
-            contest=contest,
-            inputs=inputs,
-            sandbox_directory=MODEL_DIRECTORY,
-            switch_user=False,
-        )
-        save_baseline_cache(baseline)
-    else:
-        logger.info("Using cached baseline")
-
-    logger.info("Comparing submission to baseline")
-    compare_checkpoints(
-        contest=contest,
-        submission=ModelRepositoryInfo(url=submission.get_repo_link(), revision=submission.revision),
-        inputs=inputs,
-        baseline=baseline,
-        sandbox_directory=MODEL_DIRECTORY,
-        switch_user=False,
-    )
-
-    shutil.rmtree(MODEL_DIRECTORY)
-
-
-def validate(provider: str, repository: str, revision: str, contest: Contest):
+def validate(repository: str, revision: str, contest: Contest):
     if not re.match(VALID_REPO_REGEX, repository):
         raise ValueError(f"Invalid repository URL: {repository}")
 
@@ -173,45 +76,27 @@ def validate(provider: str, repository: str, revision: str, contest: Contest):
     if repository in contest.baseline_repository.url:
         raise ValueError(f"Cannot submit baseline repository: {repository}")
 
-    if revision == contest.baseline_repository.revision:
-        raise ValueError(f"Cannot submit baseline revision: {revision}")
-
     git = cmd.Git()
     try:
-        git.ls_remote(f"https://{provider}/{repository}", revision)
+        git.ls_remote(repository, revision)
     except GitCommandError as e:
         raise ValueError(f"Invalid repository or revision: {e}")
 
 
-def get_latest_revision(provider: str, repository: str):
+def get_latest_revision(repository: str):
     git = cmd.Git()
-    return git.ls_remote(f"https://{provider}/{repository}").split()[0][:REVISION_LENGTH]
+    return git.ls_remote(repository).split()[0]
 
 
 def get_submission(config) -> CheckpointSubmission:
-    provider = config["provider"]
     repository = config["repository"]
     revision = config["revision"]
     contest_name = config["contest"]
-    contest: Contest | None = None
-
-    if contest_name:
-        try:
-            contest = find_contest(ContestId[contest_name])
-        except ValueError:
-            exit(f"Unknown contest: {contest_name}")
-
-    if not provider:
-        while True:
-            provider = input("Enter git provider (such as github.com or huggingface.co): ")
-            if re.match(VALID_PROVIDER_REGEX, provider):
-                break
-            else:
-                print("Invalid git provider.")
+    contest: Contest | None = find_contest(ContestId[contest_name]) if contest_name else None
 
     if not repository:
         while True:
-            repository = input("Enter repository URL (format: <username>/<repo>): ")
+            repository = input("Enter repository URL (format: https://<git-provider>/<username>/<repo>): ")
             if re.match(VALID_REPO_REGEX, repository):
                 break
             else:
@@ -220,7 +105,7 @@ def get_submission(config) -> CheckpointSubmission:
     if not revision:
         while True:
             try:
-                revision = input("Enter short revision hash (leave blank to fetch latest): ") or get_latest_revision(provider, repository)
+                revision = input("Enter short revision hash (leave blank to fetch latest): ") or get_latest_revision(repository)
             except GitCommandError as e:
                 exit(f"Failed to get latest revision: {e}")
             if re.match(VALID_REVISION_REGEX, revision):
@@ -229,11 +114,12 @@ def get_submission(config) -> CheckpointSubmission:
                 print("Invalid revision hash. Should be 7 characters long.")
 
     if not contest:
+        default_contest = ACTIVE_CONTESTS[0]
         while True:
             print("\nAvailable contests:")
             for c in CONTESTS:
                 print(f"\t- {c.id.name}")
-            contest_id = input(f"Enter the contest (default: {CURRENT_CONTEST.id.name}): ") or CURRENT_CONTEST.id.name
+            contest_id = input(f"Enter the contest (default: {default_contest.id.name}): ") or default_contest.id.name
             try:
                 contest = find_contest(ContestId[contest_id])
                 break
@@ -243,43 +129,45 @@ def get_submission(config) -> CheckpointSubmission:
                 print(f"Invalid contest: {contest_id}")
 
     try:
-        validate(provider, repository, revision, contest)
+        validate(repository, revision, contest)
     except ValueError as e:
         exit(f"Validation failed: {e}")
 
     return CheckpointSubmission(
-        provider=provider,
         repository=repository,
         revision=revision,
-        contest=contest.id,
+        contest_id=contest.id,
     )
 
 
-def main():
+def submit():
     config = get_config(add_extra_args)
 
     substrate = get_substrate(
         subtensor_network=config["subtensor.network"],
-        subtensor_address=config["subtensor.chain_endpoint"]
+        subtensor_address=config["subtensor.chain_endpoint"],
     )
 
-    keypair = load_hotkey_keypair(wallet_name=config["wallet.name"], hotkey_name=config["wallet.hotkey"])
+    keypair = load_hotkey_keypair(
+        wallet_name=config["wallet.name"],
+        hotkey_name=config["wallet.hotkey"],
+    )
 
     submission = get_submission(config)
     enable_benchmarking = config["benchmarking.on"]
 
     if enable_benchmarking or input("Benchmark submission before submitting? (y/N): ").strip().lower() in ("yes", "y"):
         try:
-            start_benchmarking(find_contest(submission.contest), submission)
+            start_benchmarking(find_contest(submission.contest_id), keypair, submission)
         except Exception as e:
-            exit(f"Benchmarking failed, submission cancelled: {e}")
+            logger.critical(f"Benchmarking failed, submission cancelled", exc_info=e)
+            exit(1)
 
     print(
         "\nSubmission info:\n"
-        f"Git Provider: {submission.provider}\n"
         f"Repository:   {submission.repository}\n"
         f"Revision:     {submission.revision}\n"
-        f"Contest:      {submission.contest.name}\n"
+        f"Contest:      {submission.contest_id.name}\n"
     )
     if input("Confirm submission? (Y/n): ").strip().lower() not in ("yes", "y", ""):
         exit("Submission cancelled.")
@@ -294,5 +182,9 @@ def main():
     logger.info(f"Submitted {submission} as the info for this miner")
 
 
+def main():
+    submit()
+
+
 if __name__ == '__main__':
-    main()
\ No newline at end of file
+    main()
diff --git a/miner/pyproject.toml b/miner/pyproject.toml
index e24eb4b1..ecc94e55 100644
--- a/miner/pyproject.toml
+++ b/miner/pyproject.toml
@@ -8,11 +8,11 @@ description = "The miner which provides optimized models and checkpoints"
 requires-python = ">=3.10,<3.13"
 version = "1.0.0"
 dependencies = [
-    "edge-maxxing-neuron==1.0.0"
+    "edge-maxxing-base==1.0.0"
 ]
 
 [tool.uv.sources]
-edge-maxxing-neuron = { path = "../neuron", editable = true }
+edge-maxxing-base = { path = "../base", editable = true }
 
 [dependency-groups]
 dev = [
@@ -23,7 +23,7 @@ dev = [
 inputs = ["miner"]
 
 [project.scripts]
-submit_model = 'miner.submit:main'
+submit_model = "miner.submit:main"
 
 [tool.setuptools]
 packages = [
diff --git a/miner/uv.lock b/miner/uv.lock
index 3f775ff6..55147964 100644
--- a/miner/uv.lock
+++ b/miner/uv.lock
@@ -14,7 +14,7 @@ resolution-markers = [
 
 [[package]]
 name = "accelerate"
-version = "1.1.0"
+version = "1.1.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "huggingface-hub" },
@@ -25,8 +25,9 @@ dependencies = [
     { name = "safetensors" },
     { name = "torch" },
 ]
+sdist = { url = "https://files.pythonhosted.org/packages/51/0b/179cc63d3a4f52e8cb233f2153a3e5a417522c85ea4b1dd25f6f2b377369/accelerate-1.1.1.tar.gz", hash = "sha256:0d39dfac557052bc735eb2703a0e87742879e1e40b88af8a2f9a93233d4cd7db", size = 335346 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/73/e7/e61feefda1b483f0d53a320909051252175ccbfea29ab99bd62df6083c81/accelerate-1.1.0-py3-none-any.whl", hash = "sha256:babee98bd3692cfb0537db3f96f36b5d4e29809776b406d32aaf593d4eeb574c", size = 333182 },
+    { url = "https://files.pythonhosted.org/packages/d1/d5/0050b2820a1e709ffa623f9a9e8ae42d0903535f2150613cbfeb7f16932a/accelerate-1.1.1-py3-none-any.whl", hash = "sha256:61edd81762131b8d4bede008643fa1e1f3bf59bec710ebda9771443e24feae02", size = 333211 },
 ]
 
 [[package]]
@@ -38,27 +39,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643 },
 ]
 
-[[package]]
-name = "antlr4-python3-runtime"
-version = "4.9.3"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b", size = 117034 }
-
-[[package]]
-name = "anyio"
-version = "4.6.2.post1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
-    { name = "idna" },
-    { name = "sniffio" },
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/9f/09/45b9b7a6d4e45c6bcb5bf61d19e3ab87df68e0601fa8c5293de3542546cc/anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c", size = 173422 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/e4/f5/f2b75d2fc6f1a260f340f0e7c6a060f4dd2961cc16884ed851b0d18da06a/anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d", size = 90377 },
-]
-
 [[package]]
 name = "attrs"
 version = "24.2.0"
@@ -186,18 +166,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/bf/9b/08c0432272d77b04803958a4598a51e2a4b51c06640af8b8f0f908c18bf2/charset_normalizer-3.4.0-py3-none-any.whl", hash = "sha256:fe9f97feb71aa9896b81973a7bbada8c49501dc73e58a10fcef6663af95e5079", size = 49446 },
 ]
 
-[[package]]
-name = "click"
-version = "8.1.7"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "colorama", marker = "platform_system == 'Windows'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/96/d3/f04c7bfcf5c1862a2a5b845c6b2b360488cf47af55dfa79c98f6a6bf98b5/click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de", size = 336121 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/2e/d53fa4befbf2cfa713304affc7ca780ce4fc1fd8710527771b58311a3229/click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28", size = 97941 },
-]
-
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -207,39 +175,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335 },
 ]
 
-[[package]]
-name = "cryptography"
-version = "43.0.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/69/ec/9fb9dcf4f91f0e5e76de597256c43eedefd8423aa59be95c70c4c3db426a/cryptography-43.0.0.tar.gz", hash = "sha256:b88075ada2d51aa9f18283532c9f60e72170041bba88d7f37e49cbb10275299e", size = 686873 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/d3/46/dcd2eb6840b9452e7fbc52720f3dc54a85eb41e68414733379e8f98e3275/cryptography-43.0.0-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:64c3f16e2a4fc51c0d06af28441881f98c5d91009b8caaff40cf3548089e9c74", size = 6239718 },
-    { url = "https://files.pythonhosted.org/packages/e8/23/b0713319edff1d8633775b354f8b34a476e4dd5f4cd4b91e488baec3361a/cryptography-43.0.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3dcdedae5c7710b9f97ac6bba7e1052b95c7083c9d0e9df96e02a1932e777895", size = 3808466 },
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-source = { registry = "https://pypi.org/simple" }
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-]
-
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 name = "tqdm"
-version = "4.66.6"
+version = "4.67.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "platform_system == 'Windows'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e9/34/bef135b27fe1864993a5284ad001157ee9b5538e859ac90f5b0e8cc8c9ec/tqdm-4.66.6.tar.gz", hash = "sha256:4bdd694238bef1485ce839d67967ab50af8f9272aab687c0d7702a01da0be090", size = 169533 }
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 [[package]]
 name = "transformers"
-version = "4.46.2"
+version = "4.46.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "filelock" },
@@ -2042,9 +1800,9 @@ dependencies = [
     { name = "tokenizers" },
     { name = "tqdm" },
 ]
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-[[package]]
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-version = "0.30.5"
-source = { registry = "https://pypi.org/simple" }
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-    { name = "click" },
-    { name = "h11" },
-    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
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-
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 name = "websocket-client"
 version = "1.8.0"
@@ -2197,9 +1941,9 @@ wheels = [
 
 [[package]]
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+    { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 },
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diff --git a/neuron/neuron/__init__.py b/neuron/neuron/__init__.py
deleted file mode 100644
index a043c549..00000000
--- a/neuron/neuron/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from .checkpoint import *
-from .submissions import *
-from .config import *
-from .contest import *
-from .random_inputs import *
diff --git a/neuron/neuron/checkpoint.py b/neuron/neuron/checkpoint.py
deleted file mode 100644
index b78ec6ad..00000000
--- a/neuron/neuron/checkpoint.py
+++ /dev/null
@@ -1,59 +0,0 @@
-from dataclasses import dataclass
-from typing import TypeAlias, Annotated
-
-from pydantic import BaseModel, Field
-
-from .contest import ContestId, ModelRepositoryInfo
-from .network_commitments import Encoder, Decoder
-
-Uid: TypeAlias = int
-Key: TypeAlias = str
-
-BENCHMARKS_VERSION = 15
-SPEC_VERSION = 7
-REVISION_LENGTH = 7
-
-
-@dataclass
-class GenerationOutput:
-    output: bytes
-    generation_time: float
-    vram_used: float
-    watts_used: float
-
-
-class CheckpointSubmission(BaseModel):
-    provider: str
-    repository: str
-    revision: Annotated[str, Field(min_length=REVISION_LENGTH, max_length=REVISION_LENGTH)]
-    contest: ContestId
-
-    def encode(self, encoder: Encoder):
-        encoder.write_str(self.provider)
-        encoder.write_str(self.repository)
-        encoder.write_sized_str(self.revision)
-        encoder.write_uint16(self.contest.value)
-
-    @classmethod
-    def decode(cls, decoder: Decoder):
-        provider = decoder.read_str()
-        repository = decoder.read_str()
-        revision = decoder.read_sized_str(REVISION_LENGTH)
-        contest_id = ContestId(decoder.read_uint16())
-
-        return cls(
-            provider=provider,
-            repository=repository,
-            revision=revision,
-            contest=contest_id,
-        )
-
-    def get_repo_link(self):
-        return f"https://{self.provider}/{self.repository}"
-
-
-@dataclass
-class MinerModelInfo:
-    repository: ModelRepositoryInfo
-    contest_id: ContestId
-    block: int
diff --git a/neuron/neuron/submission_tester/__init__.py b/neuron/neuron/submission_tester/__init__.py
deleted file mode 100644
index 7518e063..00000000
--- a/neuron/neuron/submission_tester/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from .setup_inference_sandbox import *
-from .inference_sandbox import *
-from .testing import *
-from .vram_monitor import *
diff --git a/neuron/neuron/submission_tester/clear_cache.sh b/neuron/neuron/submission_tester/clear_cache.sh
deleted file mode 100755
index 8674737b..00000000
--- a/neuron/neuron/submission_tester/clear_cache.sh
+++ /dev/null
@@ -1,11 +0,0 @@
-#!/bin/bash
-
-set -e
-
-cd ~/.cache
-
-find huggingface -type f -delete || true
-find pip -type f -delete || true
-find pypoetry -type f -delete || true
-find uv -type f -delete || true
-find lfs-cache -type f -delete || true
diff --git a/neuron/neuron/submission_tester/dependency_blacklist.txt b/neuron/neuron/submission_tester/dependency_blacklist.txt
deleted file mode 100644
index cbfcaa48..00000000
--- a/neuron/neuron/submission_tester/dependency_blacklist.txt
+++ /dev/null
@@ -1 +0,0 @@
-pyarmor
\ No newline at end of file
diff --git a/neuron/neuron/submission_tester/inference_sandbox.py b/neuron/neuron/submission_tester/inference_sandbox.py
deleted file mode 100644
index 76dffb56..00000000
--- a/neuron/neuron/submission_tester/inference_sandbox.py
+++ /dev/null
@@ -1,144 +0,0 @@
-import os
-from io import TextIOWrapper
-from multiprocessing.connection import Client, Connection
-from os.path import abspath
-from pathlib import Path
-from subprocess import Popen, TimeoutExpired, PIPE
-from threading import Thread
-from time import perf_counter, sleep
-from typing import Generic, TypeVar
-
-from fiber.logging_utils import get_logger
-from opentelemetry import trace
-from pydantic import BaseModel
-
-from .setup_inference_sandbox import setup_sandbox, InvalidSubmissionError, NETWORK_JAIL
-from ..contest import ModelRepositoryInfo
-
-logger = get_logger(__name__)
-tracer = trace.get_tracer(__name__)
-
-RequestT = TypeVar("RequestT", bound=BaseModel)
-
-SANDBOX = "sandbox"
-START_INFERENCE_SCRIPT = abspath(Path(__file__).parent / "start_inference.sh")
-
-
-class InferenceSandbox(Generic[RequestT]):
-    _repository: ModelRepositoryInfo
-
-    _client: Connection
-    _process: Popen
-    load_time: float
-
-    @tracer.start_as_current_span("init_inference_sandbox")
-    def __init__(
-        self,
-        repository_info: ModelRepositoryInfo,
-        baseline: bool,
-        sandbox_directory: Path,
-        switch_user: bool,
-        load_timeout: int,
-    ):
-        self._repository = repository_info
-        self._baseline = baseline
-        self._sandbox_directory = sandbox_directory
-        self._switch_user = switch_user
-
-        try:
-            with tracer.start_span("setup_sandbox"):
-                self._file_size = setup_sandbox(
-                    sandbox_args=self.sandbox_args(SANDBOX),
-                    sandbox_directory=self._sandbox_directory,
-                    baseline=baseline,
-                    url=repository_info.url,
-                    revision=repository_info.revision,
-                )
-        except InvalidSubmissionError as e:
-            self.fail(str(e))
-
-        with tracer.start_span("start_inference_process") as inference_span:
-            self._process = Popen(
-                [
-                    *self.sandbox_args(SANDBOX),
-                    START_INFERENCE_SCRIPT,
-                    NETWORK_JAIL
-                ],
-                cwd=self._sandbox_directory,
-                stdout=PIPE,
-                stderr=PIPE,
-                text=True,
-            )
-
-            Thread(target=self._stream_logs, args=(self._process.stdout,), daemon=True).start()
-            Thread(target=self._stream_logs, args=(self._process.stderr,), daemon=True).start()
-
-            logger.info("Inference process starting")
-
-            socket_path = abspath(self._sandbox_directory / "inferences.sock")
-            start = perf_counter()
-            for _ in range(load_timeout):
-                if os.path.exists(socket_path): break
-                sleep(1)
-                self._check_exit()
-            else:
-                self.fail(f"Timed out after {load_timeout} seconds")
-
-            logger.info("Connecting to socket")
-            try:
-                self._client = Client(socket_path)
-            except ConnectionRefusedError:
-                self.fail("Failed to connect to socket")
-            self.load_time = perf_counter() - start
-            inference_span.set_attribute("load_time_seconds", self.load_time)
-
-    def _check_exit(self):
-        if self._process.poll():
-            self.fail(f"Inference crashed with exit code {self._process.returncode}")
-
-    def __enter__(self):
-        self._process.__enter__()
-        self._client.__enter__()
-
-        return self
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self._client.__exit__(exc_type, exc_val, exc_tb)
-
-        self._process.terminate()
-
-        try:
-            self._process.wait(timeout=30)
-        except TimeoutExpired:
-            self._process.kill()
-            logger.warning(f"Forcefully killed inference process")
-
-        self._process.__exit__(exc_type, exc_val, exc_tb)
-
-    def __call__(self, request: RequestT):
-        self._check_exit()
-
-        data = request.model_dump_json().encode("utf-8")
-
-        self._client.send_bytes(data)
-
-        return self._client.recv_bytes()
-
-    @property
-    def model_size(self):
-        return self._file_size
-
-    def fail(self, reason: str):
-        raise InvalidSubmissionError(reason) if not self._baseline else RuntimeError(reason)
-
-    def sandbox_args(self, user: str) -> list[str]:
-        return [
-            "/bin/sudo",
-            "-u",
-            user,
-        ] if self._switch_user else []
-
-    @staticmethod
-    def _stream_logs(stream: TextIOWrapper):
-        for line in iter(stream.readline, ""):
-            logger.info(line.rstrip())
diff --git a/neuron/neuron/submission_tester/setup_inference_sandbox.py b/neuron/neuron/submission_tester/setup_inference_sandbox.py
deleted file mode 100644
index 6e39274f..00000000
--- a/neuron/neuron/submission_tester/setup_inference_sandbox.py
+++ /dev/null
@@ -1,155 +0,0 @@
-import shutil
-from os.path import abspath
-from pathlib import Path
-from subprocess import run, CalledProcessError
-
-import toml
-from fiber.logging_utils import get_logger
-from huggingface_hub import HfApi
-from opentelemetry import trace
-
-from ..checkpoint import SPEC_VERSION
-
-DEPENDENCY_BLACKLIST = abspath(Path(__file__).parent / "dependency_blacklist.txt")
-
-CLEAR_CACHE_SCRIPT = abspath(Path(__file__).parent / "clear_cache.sh")
-CLONE_SCRIPT = abspath(Path(__file__).parent / "clone.sh")
-BLACKLIST_SCRIPT = abspath(Path(__file__).parent / "blacklist.sh")
-SYNC_UV = abspath(Path(__file__).parent / "sync_uv.sh")
-DOWNLOAD_HUGGINGFACE_MODELS = abspath(Path(__file__).parent / "download_huggingface_models.sh")
-NETWORK_JAIL = abspath(Path(__file__).parent / "libnetwork_jail.so")
-
-STORAGE_THRESHOLD_GB = 50
-MAX_HF_MODEL_SIZE_GB = 100
-MAX_REPO_SIZE_MB = 16
-
-with open(DEPENDENCY_BLACKLIST, 'r') as blacklist_file:
-    BLACKLISTED_DEPENDENCIES = " ".join(blacklist_file.read().splitlines())
-
-logger = get_logger(__name__)
-tracer = trace.get_tracer(__name__)
-hf_api = HfApi()
-
-
-class InvalidSubmissionError(Exception):
-    ...
-
-
-def _run(script: str, sandbox_args: list[str], sandbox_directory: Path, args: list[str], error_message: str):
-    process = None
-    try:
-        process = run(
-            [
-                *sandbox_args,
-                script,
-                *args,
-            ],
-            capture_output=True,
-            encoding='utf-8',
-            cwd=sandbox_directory.absolute(),
-        )
-        process.check_returncode()
-    except CalledProcessError as e:
-        raise InvalidSubmissionError(error_message) from e
-    finally:
-        if process:
-            logger.info(process.stdout)
-            logger.info(process.stderr)
-
-
-def setup_sandbox(sandbox_args: list[str], sandbox_directory: Path, baseline: bool, url: str, revision: str) -> int:
-    with tracer.start_as_current_span("setup_sandbox") as span:
-        span.set_attributes({
-            "repo.url": url,
-            "repo.revision": revision
-        })
-
-        with tracer.start_as_current_span("check_disk_space") as disk_span:
-            free_space = shutil.disk_usage("/").free
-            disk_span.set_attribute("disk.free_space_gb", free_space / 1024 ** 3)
-            if free_space < STORAGE_THRESHOLD_GB * 1024 ** 3:
-                disk_span.set_attribute("cache.cleared", True)
-                with tracer.start_span("clear_cache") as cache_span:
-                    _run(
-                        CLEAR_CACHE_SCRIPT,
-                        sandbox_args,
-                        sandbox_directory,
-                        [],
-                        "Failed to clear caches"
-                    )
-                    new_free_space = shutil.disk_usage("/").free
-                    cache_span.set_attribute("cache.freed_space_gb", (new_free_space - free_space) / 1024 ** 3)
-
-        with tracer.start_span("clone_repository") as clone_span:
-            clone_span.set_attributes({
-                "repo.url": url,
-                "repo.revision": revision
-            })
-
-            _run(
-                CLONE_SCRIPT,
-                sandbox_args,
-                sandbox_directory,
-                [url, revision],
-                "Failed to clone repository"
-            )
-
-            repo_size = sum(file.stat().st_size for file in sandbox_directory.rglob("*") if ".git" not in file.parts and ".venv" not in file.parts)
-            clone_span.set_attribute("repo.size_mb", repo_size / 1024 ** 2)
-            if repo_size > MAX_REPO_SIZE_MB * 1024 ** 2:
-                raise InvalidSubmissionError(f"Size of repository exceeds {MAX_REPO_SIZE_MB} MB")
-
-            try:
-                with open(sandbox_directory / "pyproject.toml", 'r') as file:
-                    pyproject = toml.load(file)
-                    version = int(pyproject["project"]["version"])
-                    models = pyproject["tool"]["edge-maxxing"]["models"]
-            except Exception as e:
-                raise InvalidSubmissionError("Failed to read submission info") from e
-
-            clone_span.set_attribute("submission.version", version)
-            if version != SPEC_VERSION:
-                raise InvalidSubmissionError(f"Submission is at version {version} while expected version is {SPEC_VERSION}")
-
-        if not baseline:
-            with tracer.start_span("check_blacklist"):
-                _run(
-                    BLACKLIST_SCRIPT,
-                    sandbox_args,
-                    sandbox_directory,
-                    [BLACKLISTED_DEPENDENCIES],
-                    "Detected a blacklisted dependency"
-                )
-
-        with tracer.start_span("sync_uv"):
-            _run(
-                SYNC_UV,
-                sandbox_args,
-                sandbox_directory,
-                [],
-                "Failed to sync uv"
-            )
-
-        with tracer.start_span("download_huggingface_models") as hf_span:
-            try:
-                total_model_size = 0
-                for model in models:
-                    model_info = hf_api.model_info(repo_id=model, files_metadata=True)
-                    for sibling in model_info.siblings:
-                        total_model_size += sibling.size
-            except Exception as e:
-                raise InvalidSubmissionError("Failed to get model info") from e
-
-            hf_span.set_attribute("models.total_size_gb", total_model_size / 1024 ** 3)
-            if total_model_size > MAX_HF_MODEL_SIZE_GB * 1024 ** 3:
-                raise InvalidSubmissionError(f"Size of all Hugging Face models exceeds {MAX_HF_MODEL_SIZE_GB} GB")
-
-            _run(
-                DOWNLOAD_HUGGINGFACE_MODELS,
-                sandbox_args,
-                sandbox_directory,
-                [" ".join(models)],
-                "Failed to download Hugging Face models"
-            )
-
-        return repo_size + total_model_size
diff --git a/neuron/neuron/submission_tester/sync_uv.sh b/neuron/neuron/submission_tester/sync_uv.sh
deleted file mode 100755
index f50349e8..00000000
--- a/neuron/neuron/submission_tester/sync_uv.sh
+++ /dev/null
@@ -1,9 +0,0 @@
-#!/bin/bash
-
-set -e
-
-if ! ~/.local/bin/uv sync; then
-    echo "First sync attempt failed. Clearing caches and retrying..."
-    ~/.local/bin/uv cache clean
-    ~/.local/bin/uv sync
-fi
\ No newline at end of file
diff --git a/neuron/neuron/submission_tester/testing.py b/neuron/neuron/submission_tester/testing.py
deleted file mode 100644
index 4ac50ed0..00000000
--- a/neuron/neuron/submission_tester/testing.py
+++ /dev/null
@@ -1,218 +0,0 @@
-import os
-from concurrent.futures import CancelledError
-from pathlib import Path
-from statistics import mean
-from threading import Event
-from time import perf_counter
-
-from pydantic import BaseModel
-
-from fiber.logging_utils import get_logger
-from opentelemetry import trace
-
-from pipelines import TextToImageRequest
-from . import InvalidSubmissionError
-from .inference_sandbox import InferenceSandbox
-from .vram_monitor import VRamMonitor
-from .. import (
-    GenerationOutput,
-    ModelRepositoryInfo,
-    OutputComparator,
-    CheckpointBenchmark,
-    MetricData,
-    Contest,
-)
-
-SANDBOX_DIRECTORY = Path("/sandbox")
-DEFAULT_LOAD_TIMEOUT = 1000
-MIN_LOAD_TIMEOUT = 240
-
-debug = int(os.getenv("VALIDATOR_DEBUG") or 0) > 0
-logger = get_logger(__name__)
-tracer = trace.get_tracer(__name__)
-
-
-class BaselineBenchmark(BaseModel):
-    inputs: list[TextToImageRequest]
-    outputs: list[GenerationOutput]
-    metric_data: MetricData
-
-
-@tracer.start_as_current_span("generate")
-def generate(
-    contest: Contest,
-    container: InferenceSandbox,
-    request: TextToImageRequest,
-) -> GenerationOutput:
-    start_joules = contest.device.get_joules()
-    vram_monitor = VRamMonitor(contest)
-    start = perf_counter()
-
-    output = container(request)
-
-    generation_time = perf_counter() - start
-    joules_used = contest.device.get_joules() - start_joules
-    watts_used = joules_used / generation_time
-    vram_used = vram_monitor.complete()
-
-    return GenerationOutput(
-        output=output,
-        generation_time=generation_time,
-        vram_used=vram_used,
-        watts_used=watts_used,
-    )
-
-
-@tracer.start_as_current_span("generate_baseline")
-def generate_baseline(
-    contest: Contest,
-    inputs: list[TextToImageRequest],
-    sandbox_directory: Path = SANDBOX_DIRECTORY,
-    switch_user: bool = True,
-    cancelled_event: Event | None = None,
-) -> BaselineBenchmark:
-    outputs: list[GenerationOutput] = []
-
-    start_vram = contest.device.get_vram_used()
-    with InferenceSandbox(
-        repository_info=contest.baseline_repository,
-        baseline=True,
-        sandbox_directory=sandbox_directory,
-        switch_user=switch_user,
-        load_timeout=DEFAULT_LOAD_TIMEOUT,
-    ) as sandbox:
-        size = sandbox.model_size
-
-        for index, request in enumerate(inputs):
-            if cancelled_event and cancelled_event.is_set():
-                raise CancelledError()
-
-            with tracer.start_span(f"generate_sample_{index + 1}") as sample_span:
-                output = generate(contest, sandbox, request)
-                outputs.append(output)
-
-                sample_span.set_attributes({
-                    "generation.time_seconds": output.generation_time,
-                    "generation.vram_used": output.vram_used,
-                    "generation.watts_used": output.watts_used,
-                })
-
-    generation_time = mean(output.generation_time for output in outputs)
-    vram_used = max(output.vram_used for output in outputs) - start_vram
-    watts_used = max(output.watts_used for output in outputs)
-
-    return BaselineBenchmark(
-        inputs=inputs,
-        outputs=outputs,
-        metric_data=MetricData(
-            generation_time=generation_time,
-            size=size,
-            vram_used=vram_used,
-            watts_used=watts_used,
-            load_time=sandbox.load_time,
-        ),
-    )
-
-
-@tracer.start_as_current_span("compare_checkpoints")
-def compare_checkpoints(
-    contest: Contest,
-    submission: ModelRepositoryInfo,
-    inputs: list[TextToImageRequest],
-    baseline: BaselineBenchmark,
-    sandbox_directory: Path = SANDBOX_DIRECTORY,
-    switch_user: bool = True,
-    load_timeout: int = DEFAULT_LOAD_TIMEOUT,
-    cancelled_event: Event | None = None,
-) -> CheckpointBenchmark | None:
-    outputs: list[GenerationOutput] = []
-
-    start_vram = contest.device.get_vram_used()
-    with InferenceSandbox(
-            repository_info=submission,
-            baseline=False,
-            sandbox_directory=sandbox_directory,
-            switch_user=switch_user,
-            load_timeout=max(load_timeout, MIN_LOAD_TIMEOUT if not debug else DEFAULT_LOAD_TIMEOUT),
-    ) as sandbox:
-        size = sandbox.model_size
-
-        try:
-            for index, request in enumerate(inputs):
-                logger.info(f"Sample {index + 1}, prompt {request.prompt} and seed {request.seed}")
-
-                if cancelled_event and cancelled_event.is_set():
-                    raise CancelledError()
-
-                with tracer.start_span(f"generate_sample_{index + 1}") as sample_span:
-                    output = generate(contest, sandbox, request)
-                    outputs.append(output)
-
-                    sample_span.set_attributes({
-                        "generation.time_seconds": output.generation_time,
-                        "generation.vram_used": output.vram_used,
-                        "generation.watts_used": output.watts_used,
-                    })
-        except (CancelledError, TimeoutError):
-            raise
-        except Exception as e:
-            raise InvalidSubmissionError(f"Failed to run inference") from e
-
-    average_time = sum(output.generation_time for output in outputs) / len(outputs)
-    vram_used = max(output.vram_used for output in outputs) - start_vram
-    watts_used = max(output.watts_used for output in outputs)
-
-    with tracer.start_span("compare_outputs"):
-        with contest.output_comparator() as output_comparator:
-            def calculate_similarity(comparator: OutputComparator, baseline_output: GenerationOutput, optimized_output: GenerationOutput):
-                try:
-                    if cancelled_event and cancelled_event.is_set():
-                        raise CancelledError()
-
-                    return comparator(
-                        baseline_output.output,
-                        optimized_output.output,
-                    )
-                except (CancelledError, TimeoutError):
-                    raise
-                except:
-                    logger.info(
-                        f"Submission {submission.url}'s output couldn't be compared in similarity",
-                        exc_info=True,
-                    )
-
-                    return 0.0
-
-            similarities = [
-                calculate_similarity(output_comparator, baseline_output, output)
-                for baseline_output, output in zip(baseline.outputs, outputs)
-            ]
-
-            average_similarity = mean(similarities)
-            min_similarity = min(similarities)
-
-    benchmark = CheckpointBenchmark(
-        model=MetricData(
-            generation_time=average_time,
-            size=size,
-            vram_used=vram_used,
-            watts_used=watts_used,
-            load_time=sandbox.load_time,
-        ),
-        average_similarity=average_similarity,
-        min_similarity=min_similarity,
-    )
-
-    logger.info(
-        f"Tested {len(inputs)} Samples\n"
-        f"Score: {contest.calculate_score(baseline.metric_data, benchmark)}\n"
-        f"Average Similarity: {average_similarity}\n"
-        f"Min Similarity: {min_similarity}\n"
-        f"Average Generation Time: {average_time}s\n"
-        f"Model Size: {size}b\n"
-        f"Model Load Time: {sandbox.load_time}s\n"
-        f"Max VRAM Usage: {vram_used}b\n"
-        f"Max Power Usage: {watts_used}W"
-    )
-
-    return benchmark
diff --git a/neuron/neuron/submissions.py b/neuron/neuron/submissions.py
deleted file mode 100644
index 9b2b694c..00000000
--- a/neuron/neuron/submissions.py
+++ /dev/null
@@ -1,96 +0,0 @@
-from fiber.chain.commitments import publish_raw_commitment, _deserialize_commitment_field
-from fiber.logging_utils import get_logger
-from substrateinterface import SubstrateInterface, Keypair
-from substrateinterface.storage import StorageKey
-
-from .checkpoint import CheckpointSubmission, SPEC_VERSION, Key, MinerModelInfo
-from .contest import ModelRepositoryInfo, find_contest, ACTIVE_CONTESTS
-from .network_commitments import Encoder, Decoder
-
-
-logger = get_logger(__name__)
-
-
-def make_submission(
-    substrate: SubstrateInterface,
-    netuid: int,
-    keypair: Keypair,
-    submissions: list[CheckpointSubmission],
-):
-    encoder = Encoder()
-
-    encoder.write_uint16(SPEC_VERSION)
-
-    for submission in submissions:
-        submission.encode(encoder)
-
-    data = encoder.finish()
-
-    publish_raw_commitment(
-        substrate,
-        keypair,
-        netuid,
-        data,
-        wait_for_finalization=False,
-    )
-
-
-def get_submissions(
-    substrate: SubstrateInterface,
-    hotkeys: list[Key],
-    netuid: int,
-    block: int
-) -> list[MinerModelInfo | None]:
-    submissions: list[MinerModelInfo | None] = [None] * len(hotkeys)
-
-    storage_keys: list[StorageKey] = []
-    for hotkey in hotkeys:
-        storage_keys.append(substrate.create_storage_key(
-            "Commitments",
-            "CommitmentOf",
-            [netuid, hotkey]
-        ))
-
-    commitments = substrate.query_multi(
-        storage_keys=storage_keys,
-        block_hash=substrate.get_block_hash(block),
-    )
-
-    for storage, commitment in commitments:
-        hotkey = storage.params[1]
-        try:
-            if not commitment or not commitment.value:
-                continue
-
-            fields = commitment.value["info"]["fields"]
-            if not fields:
-                continue
-
-            field = _deserialize_commitment_field(fields[0])
-            if field is None:
-                continue
-
-            decoder = Decoder(field[1])
-            spec_version = decoder.read_uint16()
-            if spec_version != SPEC_VERSION:
-                continue
-
-            while not decoder.eof:
-                info = CheckpointSubmission.decode(decoder)
-                repository_url = info.get_repo_link()
-
-                if info.contest not in ACTIVE_CONTESTS:
-                    continue
-
-                if repository_url == find_contest(info.contest).baseline_repository.url:
-                    continue
-
-                repository = ModelRepositoryInfo(url=repository_url, revision=info.revision)
-                submitted_block = int(commitment.value["block"])
-                submissions[hotkeys.index(hotkey)] = MinerModelInfo(repository, info.contest, submitted_block)
-        except Exception as e:
-            logger.error(f"Failed to get submission from miner {hotkey}")
-            logger.error(f"Submission parsing error", exc_info=e)
-            continue
-
-    return submissions
\ No newline at end of file
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 1528444c..6b600fad 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -8,12 +8,7 @@ description = "Holder for models & constants to be accessed by multiple reposito
 requires-python = ">=3.10,<3.13"
 version = "1.0.0"
 dependencies = [
-    "pydantic>=2"
-]
-
-[tool.uv]
-dev-dependencies = [
-    "pytype==2024.10.11",
+    "pydantic>=2.9.2"
 ]
 
 [tool.pytype]
@@ -21,5 +16,5 @@ inputs = ["pipelines"]
 
 [tool.setuptools]
 packages = [
-    "pipelines",
+    "pipelines"
 ]
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index 0d718131..00000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,16 +0,0 @@
-[build-system]
-requires = ["setuptools >= 75.0"]
-build-backend = "setuptools.build_meta"
-
-[project]
-name = "edge-maxxing"
-description = "A Bittensor subnet designed to incentivice optimization of checkpoints and models"
-requires-python = ">=3.10,<3.13"
-version = "1.0.0"
-
-[tool.setuptools]
-packages = [
-    "neuron",
-    "validator",
-    "miner"
-]
diff --git a/validator/base_validator/__init__.py b/validator/base_validator/__init__.py
index 59fe705b..e69de29b 100644
--- a/validator/base_validator/__init__.py
+++ b/validator/base_validator/__init__.py
@@ -1,5 +0,0 @@
-from .metrics import *
-from .auto_updater import *
-from .telemetry import *
-
-API_VERSION = "5.4.0"
diff --git a/validator/base_validator/api_data.py b/validator/base_validator/api_data.py
new file mode 100644
index 00000000..17709780
--- /dev/null
+++ b/validator/base_validator/api_data.py
@@ -0,0 +1,28 @@
+from pydantic import BaseModel
+
+from base.checkpoint import Key, Uid, Benchmarks
+from base.contest import ContestId, RepositoryInfo, BenchmarkState, Metrics
+
+
+class ApiMetadata(BaseModel):
+    version: str
+    compatible_contests: set[ContestId]
+
+
+class BenchmarkingResults(BaseModel):
+    state: BenchmarkState
+    benchmarks: Benchmarks
+    invalid_submissions: set[Key]
+    baseline: Metrics | None
+    average_benchmarking_time: float | None
+
+
+class BenchmarkingStartRequest(BaseModel):
+    contest_id: ContestId
+    submissions: dict[Key, RepositoryInfo]
+
+
+class BenchmarkingInitializeRequest(BaseModel):
+    uid: Uid
+    signature: str
+    substrate_url: str
diff --git a/validator/base_validator/auto_updater.py b/validator/base_validator/auto_updater.py
index 8c7e5766..1a4462ac 100644
--- a/validator/base_validator/auto_updater.py
+++ b/validator/base_validator/auto_updater.py
@@ -1,34 +1,36 @@
 import os
 import signal
-import time
 from threading import Event, Thread
-from fiber.logging_utils import get_logger
+from time import localtime, sleep
+
 import git
+from fiber.logging_utils import get_logger
 
 UPDATE_RATE_MINUTES = 10
 
 logger = get_logger(__name__)
 
+
 class AutoUpdater:
     _thread: Thread
     _stop_flag: Event
 
     def __init__(self):
         self._stop_flag = Event()
-        self._thread = Thread(target=self._monitor, daemon=True)
+        self._thread = Thread(target=self._monitor)
         self._check_for_updates()
         self._thread.start()
 
     def _monitor(self):
         while not self._stop_flag.is_set():
             try:
-                current_time = time.localtime()
+                current_time = localtime()
                 if current_time.tm_min % UPDATE_RATE_MINUTES == 0:
                     self._check_for_updates()
-                    time.sleep(60)
+                    self._stop_flag.wait(60)
                 else:
                     sleep_minutes = UPDATE_RATE_MINUTES - current_time.tm_min % UPDATE_RATE_MINUTES
-                    time.sleep(sleep_minutes * 60 - current_time.tm_sec)
+                    self._stop_flag.wait(sleep_minutes * 60 - current_time.tm_sec)
             except Exception as e:
                 logger.error(f"Error occurred while checking for updates, attempting to fix the issue by restarting", exc_info=e)
                 self._restart()
@@ -48,15 +50,16 @@ def _check_for_updates(self):
         else:
             logger.info("Already up to date.")
 
+    def shutdown(self):
+        self._stop_flag.set()
 
     def _restart(self):
-        self._stop_flag.set()
-        time.sleep(5)
+        self.shutdown()
         os.kill(os.getpid(), signal.SIGTERM)
 
         logger.info("Waiting for process to terminate...")
         for _ in range(60):
-            time.sleep(1)
+            sleep(1)
             try:
                 os.kill(os.getpid(), 0)
             except ProcessLookupError:
diff --git a/validator/base_validator/metrics.py b/validator/base_validator/metrics.py
deleted file mode 100644
index 4f0d87f3..00000000
--- a/validator/base_validator/metrics.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from enum import Enum
-
-from pydantic import BaseModel
-
-from neuron import Key
-from neuron.contest import CheckpointBenchmark, MetricData, ContestId, ModelRepositoryInfo
-
-
-class BenchmarkState(Enum):
-    NOT_STARTED = 0
-    IN_PROGRESS = 1
-    FINISHED = 2
-
-
-class BenchmarkResults(BaseModel):
-    state: BenchmarkState
-    results: dict[Key, CheckpointBenchmark | None]
-    invalid: dict[Key, str]
-    baseline_metrics: MetricData | None
-    average_benchmark_time: float | None
-
-
-class ApiMetadata(BaseModel):
-    version: str
-    compatible_contests: list[ContestId]
-
-
-class BenchmarkingStartRequest(BaseModel):
-    contest_id: ContestId
-    submissions: dict[Key, ModelRepositoryInfo]
diff --git a/validator/base_validator/telemetry.py b/validator/base_validator/telemetry.py
index a82e57ab..05d44b4f 100644
--- a/validator/base_validator/telemetry.py
+++ b/validator/base_validator/telemetry.py
@@ -8,8 +8,15 @@
 
 ENDPOINT = "http://98.81.78.238:4317"
 
+initialized = False
+
 
 def init_open_telemetry_logging(attributes: Attributes):
+    global initialized
+    if initialized:
+        return
+    initialized = True
+
     logger_provider = LoggerProvider(resource=Resource.create(attributes=attributes))
     set_logger_provider(logger_provider)
 
diff --git a/validator/generate_compose.py b/validator/generate_compose.py
index ef3fc1b0..bf8836f6 100644
--- a/validator/generate_compose.py
+++ b/validator/generate_compose.py
@@ -49,6 +49,7 @@
       network_mode: host
 """
 
+
 def main():
     with open("compose-gpu-layout.json") as f:
         layout: list[int] = json.load(f)
diff --git a/validator/pyproject.toml b/validator/pyproject.toml
index 575b67b3..d3d0abba 100644
--- a/validator/pyproject.toml
+++ b/validator/pyproject.toml
@@ -6,17 +6,14 @@ build-backend = "setuptools.build_meta"
 name = "edge-maxxing-validator"
 description = "The validator which checks models and checkpoints provided by miners"
 requires-python = ">=3.10,<3.13"
-version = "1.0.0"
+version = "5.5.0"
 dependencies = [
-    "wandb==0.18.5",
-    "websockets==13.1",
-    "aiohttp==3.10.10",
-    "safetensors==0.4.5",
-    "edge-maxxing-neuron==1.0.0",
+    "edge-maxxing-base==1.0.0",
     "opentelemetry-api>=1.28.2",
     "opentelemetry-sdk>=1.28.2",
     "opentelemetry-exporter-otlp>=1.28.2",
     "opentelemetry-distro>=0.49b2",
+    "wandb>=0.18.7",
     "opentelemetry-instrumentation-asyncio>=0.49b2",
     "opentelemetry-instrumentation-dbapi>=0.49b2",
     "opentelemetry-instrumentation-logging>=0.49b2",
@@ -35,10 +32,13 @@ dependencies = [
     "opentelemetry-instrumentation-system-metrics>=0.49b2",
     "opentelemetry-instrumentation-tortoiseorm>=0.49b2",
     "opentelemetry-instrumentation-urllib3>=0.49b2",
+    "fastapi>=0.115.5",
+    "netaddr>=1.3.0",
+    "uvicorn>=0.32.1",
 ]
 
 [tool.uv.sources]
-edge-maxxing-neuron = { path = "../neuron", editable = true }
+edge-maxxing-base = { path = "../base", editable = true }
 
 [dependency-groups]
 dev = [
@@ -46,14 +46,18 @@ dev = [
 ]
 
 [tool.pytype]
-inputs = ["base_validator", "submission_tester", "weight_setting"]
+inputs = [
+    "base_validator",
+    "weight_setting",
+    "submission_tester",
+]
 
 [project.scripts]
-start_validator = 'weight_setting.validator:main'
+start_validator = "weight_setting.validator:main"
 
 [tool.setuptools]
 packages = [
     "base_validator",
+    "weight_setting",
     "submission_tester",
-    "weight_setting"
 ]
diff --git a/validator/submission_tester/Dockerfile b/validator/submission_tester/Dockerfile
index 44d554d6..ed6f0d56 100644
--- a/validator/submission_tester/Dockerfile
+++ b/validator/submission_tester/Dockerfile
@@ -1,36 +1,33 @@
 FROM pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime
 
-RUN apt-get update && apt-get install -y curl
+RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y sudo pipx git git-lfs build-essential python3-dev python3-opencv
 
-WORKDIR /api
+RUN useradd --create-home --home-dir /home/api api
 
-COPY neuron/pyproject.toml neuron/
-COPY neuron/neuron/__init__.py neuron/neuron/
-COPY pipelines/pyproject.toml pipelines/
-COPY pipelines/pipelines/__init__.py pipelines/pipelines/
+USER api
 
-COPY validator/pyproject.toml validator/
-COPY validator/uv.lock validator/
+RUN pipx install uv
 
-COPY validator/base_validator/__init__.py validator/base_validator/
-COPY validator/submission_tester/__init__.py validator/submission_tester/
-COPY validator/weight_setting/__init__.py validator/weight_setting/
+WORKDIR /api
 
-COPY validator/submission_tester/update.sh validator/submission_tester/
+COPY --chown=api:api pipelines/pyproject.toml ./pipelines/
+COPY --chown=api:api base/pyproject.toml ./base/
+COPY --chown=api:api validator/pyproject.toml  validator/uv.lock ./validator/
 
-RUN cd validator && ./submission_tester/update.sh
+RUN mkdir -p pipelines/pipelines
+RUN mkdir -p base/base
+RUN mkdir -p base/testing
 
-COPY README.md .
-COPY validator/submission_tester/start.sh validator/submission_tester/
+WORKDIR /api/validator
+RUN ~/.local/bin/uv sync --compile-bytecode --no-dev --frozen --no-install-project --no-install-workspace
+WORKDIR /api
 
+COPY pipelines pipelines
+COPY base base
+COPY validator validator
 COPY --chown=api:api .git .git
-COPY validator/base_validator validator/base_validator
-COPY validator/submission_tester validator/submission_tester
-COPY neuron/neuron neuron/neuron
-COPY pipelines/pipelines pipelines/pipelines
 
 WORKDIR /api/validator
-
+USER root
 EXPOSE 8000
-
 ENTRYPOINT ["submission_tester/entrypoint.sh"]
diff --git a/validator/submission_tester/api.py b/validator/submission_tester/api.py
index 474a8999..b6a6e15b 100644
--- a/validator/submission_tester/api.py
+++ b/validator/submission_tester/api.py
@@ -1,25 +1,22 @@
 import os
-import time
 from contextlib import asynccontextmanager
+from importlib.metadata import version
+from pathlib import Path
+from time import time_ns
 from typing import Annotated
 
-from fastapi import Body
-from fastapi import FastAPI, Request, Header, HTTPException
+from fastapi import FastAPI, HTTPException
+from fastapi.params import Header, Body
 from fiber.logging_utils import get_logger
-from starlette import status
+from starlette.requests import Request
+from starlette.status import HTTP_403_FORBIDDEN, HTTP_400_BAD_REQUEST, HTTP_429_TOO_MANY_REQUESTS
 from substrateinterface import Keypair
 
-from base_validator import (
-    API_VERSION,
-    BenchmarkState,
-    BenchmarkResults,
-    AutoUpdater,
-    ApiMetadata, BenchmarkingStartRequest,
-    init_open_telemetry_logging,
-)
-from neuron import CURRENT_CONTEST
-from neuron import find_compatible_contests, find_contest
-from .benchmarker import Benchmarker
+from base.contest import find_compatible_contests, find_contest, CONTESTS
+from base_validator.api_data import BenchmarkingStartRequest, BenchmarkingResults, ApiMetadata, BenchmarkingInitializeRequest
+from base_validator.auto_updater import AutoUpdater
+from base_validator.telemetry import init_open_telemetry_logging
+from testing.benchmarker import Benchmarker
 
 hotkey = os.getenv("VALIDATOR_HOTKEY_SS58_ADDRESS")
 debug = int(os.getenv("VALIDATOR_DEBUG") or 0) > 0
@@ -29,27 +26,32 @@
 
 keypair = Keypair(ss58_address=hotkey)
 
-init_open_telemetry_logging({
-    "neuron.hotkey": hotkey,
-    "api.version": API_VERSION,
-})
+api_version = version("edge-maxxing-validator")
 
 logger = get_logger(__name__)
 
 
 @asynccontextmanager
 async def lifespan(_: FastAPI):
-    AutoUpdater()
+    auto_updater = AutoUpdater()
 
-    compatible_contests = find_compatible_contests() if not debug else [CURRENT_CONTEST.id]
+    compatible_contests = find_compatible_contests() if not debug else [contest.id for contest in CONTESTS]
     if not compatible_contests:
         raise RuntimeError("Device is not compatible with any contests")
 
+    benchmarker = Benchmarker(
+        sandbox_directory=Path("/sandbox"),
+        sandbox_args=["/bin/sudo", "-u", "sandbox"]
+    )
+
     yield {
-        "benchmarker": Benchmarker(),
+        "benchmarker": benchmarker,
         "compatible_contests": compatible_contests,
     }
 
+    benchmarker.shutdown()
+    auto_updater.shutdown()
+
 
 app = FastAPI(lifespan=lifespan)
 
@@ -58,13 +60,13 @@ def _authenticate_request(nonce: int, signature: str):
     if debug:
         return
 
-    current_timestamp = time.time_ns()
+    current_timestamp = time_ns()
 
     if current_timestamp - nonce > 2_000_000_000:
         logger.info(f"Got request with nonce {nonce}, which is {current_timestamp - nonce} nanoseconds old.")
 
         raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
+            status_code=HTTP_403_FORBIDDEN,
             detail="Invalid nonce",
         )
 
@@ -72,14 +74,14 @@ def _authenticate_request(nonce: int, signature: str):
         logger.info(f"Got invalid signature for nonce {nonce}: {signature}")
 
         raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
+            status_code=HTTP_403_FORBIDDEN,
             detail="Invalid signature",
         )
 
 
 @app.post("/start")
-def start_benchmarking(
-    benchmarking_start_request: Annotated[BenchmarkingStartRequest, Body()],
+def start(
+    start_request: Annotated[BenchmarkingStartRequest, Body()],
     x_nonce: Annotated[int, Header()],
     signature: Annotated[str, Header()],
     request: Request,
@@ -88,61 +90,56 @@ def start_benchmarking(
 
     benchmarker: Benchmarker = request.state.benchmarker
 
-    with benchmarker.lock:
-        timestamp = time.time_ns()
-
-        try:
-            contest = find_contest(benchmarking_start_request.contest_id)
-            if not debug:
-                contest.device.validate()
-        except Exception as e:
-            raise HTTPException(
-                status_code=status.HTTP_400_BAD_REQUEST,
-                detail=str(e),
-            )
-
-        if timestamp - benchmarker.start_timestamp < 120_000_000_000:
-            raise HTTPException(
-                status_code=status.HTTP_429_TOO_MANY_REQUESTS,
-                detail="Started recently",
-            )
+    contest = find_contest(start_request.contest_id)
+    if not debug and not contest.device.is_compatible():
+        raise HTTPException(
+            status_code=HTTP_400_BAD_REQUEST,
+            detail=str("API is not compatible with contest"),
+        )
 
-        benchmarker.start_timestamp = timestamp
+    timestamp = time_ns()
+    if timestamp - benchmarker.start_timestamp < 10_000_000_000:
+        raise HTTPException(
+            status_code=HTTP_429_TOO_MANY_REQUESTS,
+            detail="Started recently",
+        )
 
-        benchmarker.start_benchmarking(contest, benchmarking_start_request.submissions)
+    benchmarker.start_timestamp = timestamp
+    benchmarker.start_benchmarking(contest, start_request.submissions)
 
 
 @app.get("/state")
-def state(request: Request) -> BenchmarkResults:
+def state(request: Request) -> BenchmarkingResults:
     benchmarker: Benchmarker = request.state.benchmarker
 
-    benchmark_state: BenchmarkState
-
-    if not benchmarker.thread:
-        benchmark_state = BenchmarkState.NOT_STARTED
-    elif benchmarker.done:
-        benchmark_state = BenchmarkState.FINISHED
-    else:
-        benchmark_state = BenchmarkState.IN_PROGRESS
-
-    average_benchmark_time = (
-        sum(benchmarker.submission_times) / len(benchmarker.submission_times)
-        if benchmarker.submission_times
-        else None
-    )
-
-    return BenchmarkResults(
-        state=benchmark_state,
-        results=benchmarker.benchmarks,
-        invalid=benchmarker.invalid,
-        baseline_metrics=benchmarker.get_baseline_metrics(),
-        average_benchmark_time=average_benchmark_time,
+    return BenchmarkingResults(
+        state=benchmarker.state,
+        benchmarks=benchmarker.benchmarks,
+        invalid_submissions=benchmarker.invalid_submissions,
+        baseline=benchmarker.baseline.metrics if benchmarker.baseline else None,
+        average_benchmarking_time=benchmarker.get_average_benchmarking_time(),
     )
 
 
 @app.get("/metadata")
 def metadata(request: Request) -> ApiMetadata:
     return ApiMetadata(
-        version=API_VERSION,
+        version=api_version,
         compatible_contests=request.state.compatible_contests,
     )
+
+
+@app.post("/initialize")
+def initialize(
+    init_request: Annotated[BenchmarkingInitializeRequest, Body()],
+    x_nonce: Annotated[int, Header()],
+    signature: Annotated[str, Header()],
+):
+    _authenticate_request(x_nonce, signature)
+
+    init_open_telemetry_logging({
+        "neuron.uid": init_request.uid,
+        "neuron.signature": init_request.signature,
+        "subtensor.chain_endpoint": init_request.substrate_url,
+        "api.version": api_version,
+    })
diff --git a/validator/submission_tester/benchmarker.py b/validator/submission_tester/benchmarker.py
deleted file mode 100644
index e10d0a1e..00000000
--- a/validator/submission_tester/benchmarker.py
+++ /dev/null
@@ -1,163 +0,0 @@
-from concurrent.futures import CancelledError
-from random import choice
-from threading import Lock, Event, Thread
-from time import perf_counter, sleep
-from typing import cast
-
-from fiber.logging_utils import get_logger
-from opentelemetry import trace
-
-from neuron import (
-    Key,
-    ModelRepositoryInfo,
-    random_inputs,
-    Contest,
-)
-from neuron.submission_tester import (
-    CheckpointBenchmark,
-    BaselineBenchmark,
-    MetricData,
-    compare_checkpoints,
-    generate_baseline,
-    InvalidSubmissionError,
-)
-from pipelines import TextToImageRequest
-
-logger = get_logger(__name__)
-tracer = trace.get_tracer(__name__)
-
-
-class Benchmarker:
-    contest: Contest | None
-    submissions: dict[Key, ModelRepositoryInfo]
-    benchmarks: dict[Key, CheckpointBenchmark | None]
-    invalid: dict[Key, str]
-    baseline: BaselineBenchmark | None
-    inputs: list[TextToImageRequest]
-    started: bool
-    done: bool
-    start_timestamp: int
-    submission_times: list[float]
-    thread: Thread | None
-    lock: Lock
-    cancelled_event: Event
-
-    def __init__(self):
-        self.contest = None
-        self.submissions = {}
-        self.benchmarks = {}
-        self.invalid = {}
-        self.baseline = None
-        self.inputs = []
-        self.done = False
-        self.start_timestamp = 0
-        self.thread = None
-        self.lock = Lock()
-        self.submission_times = []
-        self.cancelled_event = Event()
-
-    def _benchmark_submission(self, hotkey: Key):
-        with tracer.start_as_current_span("benchmark_submission") as span:
-            submission = self.submissions[hotkey]
-            span.set_attributes({
-                "submission.hotkey": str(hotkey),
-                "submission.url": submission.url,
-                "submission.revision": submission.revision
-            })
-
-            start_time = perf_counter()
-
-            try:
-                self.benchmarks[hotkey] = compare_checkpoints(
-                    contest=self.contest,
-                    submission=submission,
-                    inputs=self.inputs,
-                    baseline=self.baseline,
-                    load_timeout=int(cast(MetricData, self.get_baseline_metrics()).load_time * 2),
-                    cancelled_event=self.cancelled_event,
-                )
-            except InvalidSubmissionError as e:
-                logger.error(f"Skipping invalid submission '{submission}': '{e}'")
-                self.benchmarks[hotkey] = None
-                self.invalid[hotkey] = str(e)
-            except CancelledError:
-                logger.warning(f"Benchmarking was canceled while testing '{submission}'")
-                raise
-            except Exception as e:
-                span.record_exception(e)
-            finally:
-                duration = perf_counter() - start_time
-                self.submission_times.append(duration)
-                span.set_attribute("benchmark.duration_seconds", duration)
-
-    def _start_benchmarking(self, contest: Contest, submissions: dict[Key, ModelRepositoryInfo]):
-        with tracer.start_as_current_span("start_benchmarking") as span:
-            span.set_attribute("submissions.total", len(submissions))
-
-            self.contest = contest
-            self.submissions = submissions
-            self.benchmarks.clear()
-            self.invalid.clear()
-            self.submission_times.clear()
-            self.inputs = random_inputs()
-            self.done = False
-            self.baseline = None
-
-            with tracer.start_span("generate_baseline"):
-                while not self.baseline and not self.cancelled_event.is_set():
-                    try:
-                        logger.info("Generating baseline samples to compare")
-                        self.baseline = generate_baseline(
-                            contest=contest,
-                            inputs=self.inputs,
-                            cancelled_event=self.cancelled_event
-                        )
-                    except CancelledError:
-                        logger.warning("Benchmarking was canceled while testing the baseline")
-                        return
-                    except Exception as e:
-                        logger.error("Failed to generate baseline samples, retrying in 10 minutes", exc_info=e)
-                        sleep(600)
-
-            with tracer.start_span("benchmark_submissions") as bench_span:
-                while len(self.benchmarks) != len(self.submissions) and self.baseline and not self.cancelled_event.is_set():
-                    hotkey = choice(list(self.submissions.keys() - self.benchmarks.keys()))
-                    self._benchmark_submission(hotkey)
-
-                    valid_submissions = len([benchmark for benchmark in self.benchmarks.values() if benchmark])
-                    bench_span.set_attributes({
-                        "progress.total": len(self.benchmarks),
-                        "progress.valid": valid_submissions,
-                    })
-                    logger.info(f"{len(self.benchmarks)}/{len(self.submissions)} submissions benchmarked. {valid_submissions} valid.")
-
-            logger.info("Benchmarking complete")
-            self.done = True
-
-    @tracer.start_as_current_span("start_benchmarking")
-    def start_benchmarking(self, contest: Contest, submissions: dict[Key, ModelRepositoryInfo]):
-        if not submissions:
-            logger.warning("No submissions to benchmark")
-            return
-
-        logger.info(f"Starting benchmarking for {len(submissions)} submissions")
-
-        if self.thread and self.thread.is_alive():
-            logger.info("Attempting to cancel previous benchmarking")
-            self.cancelled_event.set()
-            self.thread.join(timeout=60)
-            if self.thread.is_alive():
-                logger.warning("Benchmarking was not stopped gracefully.")
-            else:
-                logger.info("Benchmarking was stopped gracefully.")
-
-        self.cancelled_event.clear()
-        self.thread = Thread(
-            target=self._start_benchmarking,
-            args=(contest, submissions,),
-            daemon=True,
-        )
-        self.thread.start()
-
-    def get_baseline_metrics(self) -> MetricData | None:
-        return self.baseline.metric_data if self.baseline else None
diff --git a/validator/submission_tester/start.sh b/validator/submission_tester/start.sh
index 86f96881..2d78c973 100755
--- a/validator/submission_tester/start.sh
+++ b/validator/submission_tester/start.sh
@@ -7,5 +7,5 @@ set -e
 sudo -u api /home/api/.local/bin/uv run opentelemetry-instrument \
   --service_name edge-maxxing-api \
   --exporter_otlp_endpoint http://98.81.78.238:4317 \
-  --resource_attributes "neuron.type=validator" \
+  --resource_attributes "neuron.type=validator,neuron.hotkey=$VALIDATOR_HOTKEY_SS58_ADDRESS" \
   uvicorn "$@"
diff --git a/validator/submission_tester/update.sh b/validator/submission_tester/update.sh
index da505c94..03b98f71 100755
--- a/validator/submission_tester/update.sh
+++ b/validator/submission_tester/update.sh
@@ -5,12 +5,12 @@ set -e
 apt-get update
 DEBIAN_FRONTEND=noninteractive apt-get -y install sudo pipx git git-lfs build-essential python3-dev python3-opencv
 
-if ! id -u api &>/dev/null; then
-  useradd --shell=/bin/false --create-home --home-dir /home/sandbox sandbox || true
-  useradd --create-home --home-dir /home/api api || true
-fi
+useradd --create-home --home-dir /home/api api || true
+useradd --shell=/bin/false --create-home --home-dir /home/sandbox sandbox || true
 
-chown -R api:api /api
+chown -R api:api /api/.git
+chown api:api /api/validator/.venv
+chown api:api /api/validator/uv.lock
 
 pkill -9 -u sandbox || true
 pkill -9 -u api || true
@@ -20,21 +20,30 @@ rm -rf /sandbox
 mkdir /sandbox
 chown sandbox:sandbox /sandbox
 
+mkdir -p /home/sandbox/.local
+chown sandbox:sandbox /home/sandbox/.local
+mkdir -p /home/sandbox/.cache
+chown sandbox:sandbox /home/sandbox/.cache
+
+if [ -z "$CUDA_VISIBLE_DEVICES" ]; then
+  unset CUDA_VISIBLE_DEVICES
+fi
+
 echo "root ALL=(ALL:ALL) ALL" > /etc/sudoers
 echo "api ALL = (sandbox) NOPASSWD: ALL" >> /etc/sudoers
 echo "Defaults env_keep += \"VALIDATOR_HOTKEY_SS58_ADDRESS VALIDATOR_DEBUG CUDA_VISIBLE_DEVICES\"" >> /etc/sudoers
 
-git config --system --add safe.directory '*'
 git config --system advice.detachedHead false
+git config --system --add safe.directory '*'
 git config --system rebase.autostash true
 git config --system rebase.autosquash true
 git config --system pull.autostash true
 
 sudo -u api pipx ensurepath
 sudo -u api pipx install uv
-sudo -u api /home/api/.local/bin/uv sync
+sudo -u api /home/api/.local/bin/uv sync --no-dev --frozen
 
 sudo -u sandbox pipx ensurepath
 sudo -u sandbox pipx install uv
 sudo -u sandbox pipx install huggingface-hub[cli,hf_transfer]
-sudo -u sandbox pipx upgrade-all
+
diff --git a/validator/uv.lock b/validator/uv.lock
index 8d2aa6b8..0cf8a2a1 100644
--- a/validator/uv.lock
+++ b/validator/uv.lock
@@ -2,28 +2,28 @@ version = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
     "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform != 'linux'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform != 'linux'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and platform_system == 'Darwin' and sys_platform != 'linux'",
-    "python_full_version >= '3.12' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
-    "(python_full_version >= '3.12' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version >= '3.12' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
     "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
     "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
     "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux')",
+    "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform != 'linux'",
     "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
     "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
     "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux')",
+    "python_full_version >= '3.12' and platform_system == 'Darwin' and sys_platform != 'linux'",
     "python_full_version >= '3.12' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'linux'",
     "python_full_version >= '3.12' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'linux') or (python_full_version >= '3.12' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')",
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+    { name = "pynvml", specifier = ">=11.5.3" },
+    { name = "scikit-image", specifier = ">=0.24.0" },
+    { name = "transformers", specifier = ">=4.46.3" },
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@@ -519,18 +379,16 @@ dependencies = [
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 [package.metadata]
-requires-dist = [{ name = "pydantic", specifier = ">=2" }]
-
-[package.metadata.requires-dev]
-dev = [{ name = "pytype", specifier = "==2024.10.11" }]
+requires-dist = [{ name = "pydantic", specifier = ">=2.9.2" }]
 
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-version = "1.0.0"
+version = "5.5.0"
 source = { editable = "." }
 dependencies = [
-    { name = "aiohttp" },
-    { name = "edge-maxxing-neuron" },
+    { name = "edge-maxxing-base" },
+    { name = "fastapi" },
+    { name = "netaddr" },
     { name = "opentelemetry-api" },
     { name = "opentelemetry-distro" },
     { name = "opentelemetry-exporter-otlp" },
@@ -553,9 +411,8 @@ dependencies = [
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     { name = "opentelemetry-instrumentation-wsgi" },
     { name = "opentelemetry-sdk" },
-    { name = "safetensors" },
+    { name = "uvicorn" },
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-    { name = "websockets" },
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@@ -565,8 +422,9 @@ dev = [
 
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-    { name = "edge-maxxing-neuron", editable = "../neuron" },
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-    { name = "cryptography" },
     { name = "eth-typing" },
-    { name = "fastapi" },
-    { name = "httpx" },
-    { name = "netaddr" },
+    { name = "pydantic" },
     { name = "python-dotenv" },
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-
 [[package]]
 name = "zipp"
-version = "3.20.2"
+version = "3.21.0"
 source = { registry = "https://pypi.org/simple" }
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+sdist = { url = "https://files.pythonhosted.org/packages/3f/50/bad581df71744867e9468ebd0bcd6505de3b275e06f202c2cb016e3ff56f/zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", size = 24545 }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 },
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diff --git a/validator/weight_setting/Dockerfile b/validator/weight_setting/Dockerfile
index 9a2ca363..05fce371 100644
--- a/validator/weight_setting/Dockerfile
+++ b/validator/weight_setting/Dockerfile
@@ -1,43 +1,36 @@
 FROM python:3.10
 
-RUN apt-get update && apt-get install -y sudo pipx
+RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y sudo pipx git
 
 RUN useradd --create-home --home-dir /home/validator validator
 
-WORKDIR /app
-
 USER validator
 
 RUN pipx install uv
 
-COPY neuron/pyproject.toml neuron/
-COPY neuron/neuron/__init__.py neuron/neuron/
-COPY pipelines/pyproject.toml pipelines/
-COPY pipelines/pipelines/__init__.py pipelines/pipelines/
+WORKDIR /app
 
-COPY validator/pyproject.toml validator/
-COPY validator/uv.lock validator/
+COPY --chown=validator:validator pipelines/pyproject.toml ./pipelines/
+COPY --chown=validator:validator base/pyproject.toml ./base/
+COPY --chown=validator:validator validator/pyproject.toml  validator/uv.lock ./validator/
 
-COPY README.md .
+RUN mkdir -p pipelines/pipelines
+RUN mkdir -p base/base
+RUN mkdir -p base/testing
 
-COPY validator/base_validator/__init__.py validator/base_validator/
-COPY validator/submission_tester/__init__.py validator/submission_tester/
-COPY validator/weight_setting/__init__.py validator/weight_setting/
-COPY --chown=api:api .git .git
+WORKDIR /app/validator
+RUN ~/.local/bin/uv sync --compile-bytecode --no-dev --frozen --no-install-project --no-install-workspace
+WORKDIR /app
 
-USER root
-RUN chown -R validator:validator /app
-USER validator
+COPY pipelines pipelines
+COPY base base
+COPY validator validator
+COPY --chown=validator:validator .git .git
 
 WORKDIR /app/validator
-ENV PATH="/home/validator/.local/bin:$PATH"
 
-RUN uv sync
+USER root
 
-COPY validator/base_validator base_validator
-COPY validator/weight_setting weight_setting
-COPY neuron/neuron ../neuron/neuron
-COPY pipelines/pipelines ../pipelines/pipelines
+RUN chown validator:validator uv.lock
 
-USER root
-ENTRYPOINT ["weight_setting/entrypoint.sh"]
\ No newline at end of file
+ENTRYPOINT ["weight_setting/entrypoint.sh"]
diff --git a/validator/weight_setting/benchmarking_api.py b/validator/weight_setting/benchmarking_api.py
index 3bb6dd5b..2a4c75df 100644
--- a/validator/weight_setting/benchmarking_api.py
+++ b/validator/weight_setting/benchmarking_api.py
@@ -1,40 +1,45 @@
-import time
+from collections import defaultdict
 from itertools import islice
 from math import ceil
+from operator import itemgetter
+from time import time_ns
 
 import requests
 from fiber.logging_utils import get_logger
 from substrateinterface import Keypair
 
-from base_validator import BenchmarkResults, BenchmarkingStartRequest, ApiMetadata, API_VERSION
-from neuron import ModelRepositoryInfo, Key, ContestId, MinerModelInfo, CURRENT_CONTEST
+from base.checkpoint import Key, Uid, Submissions
+from base.contest import ContestId, RepositoryInfo, ACTIVE_CONTESTS
+from base_validator.api_data import BenchmarkingStartRequest, ApiMetadata, BenchmarkingResults, BenchmarkingInitializeRequest
 
 logger = get_logger(__name__)
 
 
-def _authentication_headers(keypair: Keypair):
-    nonce = str(time.time_ns())
-
-    signature = f"0x{keypair.sign(nonce).hex()}"
-
-    return {
-        "X-Nonce": nonce,
-        "Signature": signature,
-    }
-
-
 class BenchmarkingApi:
-    _keypair: Keypair
     _api: str
+    _keypair: Keypair
 
-    def __init__(self, keypair: Keypair, api: str):
-        self._keypair = keypair
+    def __init__(self, api: str, keypair: Keypair):
         self._api = api
+        self._keypair = keypair
 
-    def start_benchmarking(self, contest_id: ContestId, submissions: dict[Key, ModelRepositoryInfo]):
-        logger.info(f"Sending {len(submissions)} submissions for testing")
+    def initialize(self, uid: Uid, signature: str, substrate_url: str):
+        requests.post(
+            f"{self._api}/initialize",
+            headers={
+                "Content-Type": "application/json",
+                **_authentication_headers(self._keypair),
+            },
+            data=BenchmarkingInitializeRequest(
+                uid=uid,
+                signature=signature,
+                substrate_url=substrate_url,
+            ).model_dump_json(),
+
+        ).raise_for_status()
 
-        data = BenchmarkingStartRequest(contest_id=contest_id, submissions=submissions)
+    def start(self, contest_id: ContestId, submissions: dict[Key, RepositoryInfo]):
+        logger.info(f"Sending {len(submissions)} submissions for {contest_id.name}")
 
         requests.post(
             f"{self._api}/start",
@@ -42,34 +47,79 @@ def start_benchmarking(self, contest_id: ContestId, submissions: dict[Key, Model
                 "Content-Type": "application/json",
                 **_authentication_headers(self._keypair),
             },
-            data=data.model_dump_json(),
+            data=BenchmarkingStartRequest(
+                contest_id=contest_id,
+                submissions=submissions,
+            ).model_dump_json(),
         ).raise_for_status()
 
-    def state(self):
-        response = requests.get(f"{self._api}/state")
-        response.raise_for_status()
-        return BenchmarkResults.model_validate(response.json())
-
     def metadata(self) -> ApiMetadata:
         response = requests.get(f"{self._api}/metadata")
         response.raise_for_status()
         return ApiMetadata.model_validate(response.json())
 
+    def results(self) -> BenchmarkingResults:
+        response = requests.get(f"{self._api}/state")
+        response.raise_for_status()
+        return BenchmarkingResults.model_validate(response.json())
+
+
+def _authentication_headers(keypair: Keypair):
+    nonce = str(time_ns())
 
-def send_submissions_to_api(apis: list[BenchmarkingApi], submissions: dict[Key, MinerModelInfo]):
-    submissions_info = {
-        key: info.repository
-        for key, info in submissions.items()
+    signature = f"0x{keypair.sign(nonce).hex()}"
+
+    return {
+        "X-Nonce": nonce,
+        "Signature": signature,
     }
 
-    iterator = iter(submissions_info.items())
 
-    chunk_size = ceil(len(submissions_info) / len(apis))
+def send_submissions_to_api(version: str, all_apis: list[BenchmarkingApi], submissions: Submissions):
+    submissions_by_contest: dict[ContestId, dict[Key, RepositoryInfo]] = defaultdict(lambda: {})
+
+    for key, submission in submissions.items():
+        submissions_by_contest[submission.contest_id][key] = submission.repository_info
+
+    contest_api_assignment: dict[ContestId, list[BenchmarkingApi]] = defaultdict(lambda: [])
+
+    for api in all_apis:
+        metadata = api.metadata()
+        if metadata.version != version:
+            raise ValueError(f"API version mismatch, expected {version}, got {metadata.version}")
+
+        if sum(len(contest_api_assignment[contest_id]) for contest_id in metadata.compatible_contests) == 0:
+            compatible_contests = list(filter(submissions_by_contest.__contains__, metadata.compatible_contests))
+
+            if compatible_contests:
+                contest_api_assignment[compatible_contests[0]].append(api)
+        else:
+            assignment_counts = [
+                (contest_id, len(contest_api_assignment[contest_id]))
+                for contest_id in metadata.compatible_contests
+                if contest_id in submissions_by_contest
+            ]
+
+            lowest_contest_id = min(assignment_counts, key=itemgetter(1))[0]
+
+            contest_api_assignment[lowest_contest_id].append(api)
+
+    for contest_id, apis in contest_api_assignment.items():
+        if not contest_id in ACTIVE_CONTESTS:
+            continue
+        if contest_id not in submissions_by_contest:
+            raise RuntimeError(f"No API compatible with contest type {contest_id.name}")
+
+        contest_submissions = submissions_by_contest[contest_id]
+
+        iterator = iter(contest_submissions.items())
+
+        chunk_size = ceil(len(contest_submissions) / len(apis))
 
-    chunks = [
-        (api, list(islice(iterator, chunk_size)))
-        for api in apis
-    ]
+        chunks = [
+            (api, list(islice(iterator, chunk_size)))
+            for api in apis
+        ]
 
-    for api, chunk in chunks:
-        api.start_benchmarking(CURRENT_CONTEST.id, dict(chunk))
+        for api, chunk in chunks:
+            api.start(contest_id, dict(chunk))
diff --git a/validator/weight_setting/contest_state.py b/validator/weight_setting/contest_state.py
new file mode 100644
index 00000000..80a1e080
--- /dev/null
+++ b/validator/weight_setting/contest_state.py
@@ -0,0 +1,97 @@
+from datetime import datetime, timedelta
+from threading import Event
+
+from fiber.logging_utils import get_logger
+from pydantic import BaseModel, ConfigDict
+
+from base.checkpoint import Key, current_time, Submissions, Benchmarks
+from base.contest import Metrics, BenchmarkState
+from weight_setting.winner_selection import get_contestant_scores, get_contestant_ranks, calculate_rank_weights
+
+logger = get_logger(__name__)
+
+
+class ContestState(BaseModel):
+    model_config = ConfigDict(extra="ignore")
+    step: int
+    benchmarks_version: int
+    submissions: Submissions
+    benchmarks: Benchmarks
+    baseline: Metrics | None
+    invalid_submissions: set[Key]
+    last_benchmarks: Benchmarks
+    average_benchmarking_time: float | None
+    benchmarking_state: BenchmarkState
+    contest_end: datetime
+
+    def start_new_contest(self, benchmarks_version: int, submissions: Submissions):
+        self.benchmarks_version = benchmarks_version
+        self.submissions = submissions
+
+        self.last_benchmarks = self.benchmarks
+        self.benchmarks.clear()
+        self.baseline = None
+        self.average_benchmarking_time = None
+
+        now = current_time()
+        end_time = now.replace(hour=12, minute=0, second=0, microsecond=0)
+        if now.hour >= 12:
+            end_time += timedelta(days=1)
+        self.contest_end = end_time
+
+    def get_contest_start(self) -> datetime:
+        return self.contest_end - timedelta(days=1)
+
+    def is_ended(self) -> bool:
+        now = current_time()
+        return now >= self.contest_end or not self.submissions
+
+    def get_untested_submissions(self) -> Submissions:
+        return {
+            key: submission for key, submission in self.submissions.items()
+            if key not in self.benchmarks and key not in self.invalid_submissions
+        }
+
+    def sleep_to_next_contest(self, stop_flag: Event):
+        now = current_time()
+        next_contest_time = self.contest_end - now
+        logger.info(f"Sleeping until next contest: {next_contest_time}")
+        stop_flag.wait(next_contest_time.total_seconds())
+
+    def get_scores(self) -> dict[Key, float]:
+        if not self.baseline:
+            return {}
+
+        return get_contestant_scores(
+            submissions=self.submissions,
+            benchmarks=self.benchmarks,
+            baseline=self.baseline,
+        )
+
+    def get_ranks(self, scores: dict[Key, float]) -> dict[Key, int]:
+        return get_contestant_ranks(scores=scores)
+
+    def calculate_weights(self, ranks: dict[Key, int]):
+        return calculate_rank_weights(
+            submitted_blocks={
+                key: submission.block
+                for key, submission in self.submissions.items()
+            },
+            ranks=ranks,
+        )
+
+    @classmethod
+    def create(cls, benchmarks_version: int):
+        state = cls(
+            step=0,
+            benchmarks_version=benchmarks_version,
+            submissions={},
+            benchmarks={},
+            baseline=None,
+            invalid_submissions=set(),
+            last_benchmarks={},
+            average_benchmarking_time=None,
+            benchmarking_state=BenchmarkState.NOT_STARTED,
+            contest_end=current_time()
+        )
+        return state
diff --git a/validator/weight_setting/start.sh b/validator/weight_setting/start.sh
index eab097f6..5aed1bf5 100755
--- a/validator/weight_setting/start.sh
+++ b/validator/weight_setting/start.sh
@@ -2,7 +2,7 @@
 
 set -e
 
-~/.local/bin/uv run opentelemetry-instrument \
+~/.local/bin/uv run --no-dev --frozen opentelemetry-instrument \
   --service_name edge-maxxing-validator \
   --exporter_otlp_endpoint http://98.81.78.238:4317 \
   --resource_attributes "neuron.type=validator,$(~/.local/bin/uv run python3 weight_setting/telemetry_attributes.py "$@")" \
diff --git a/validator/weight_setting/state_manager.py b/validator/weight_setting/state_manager.py
new file mode 100644
index 00000000..7c1c658d
--- /dev/null
+++ b/validator/weight_setting/state_manager.py
@@ -0,0 +1,47 @@
+from pathlib import Path
+
+from fiber.logging_utils import get_logger
+from pydantic_core import ValidationError
+
+from .contest_state import ContestState
+
+logger = get_logger(__name__)
+
+STATE_VERSION = 2
+
+
+class StateManager:
+    _state_file: Path
+
+    def __init__(self, wallet_name: str, hotkey_name: str, netuid: int):
+        path = (
+            Path.home() /
+            ".bittensor" /
+            "miners" /
+            wallet_name /
+            hotkey_name /
+            f"netuid{netuid}" /
+            "validator"
+        )
+
+        path.mkdir(parents=True, exist_ok=True)
+        self._state_file = path / f"state_v{STATE_VERSION}.json"
+
+    def load_state(self) -> ContestState | None:
+        if not self._state_file.exists():
+            return None
+
+        logger.info(f"Loading state")
+
+        try:
+            with self._state_file.open("rb") as file:
+                return ContestState.model_validate_json(file.read())
+        except ValidationError as e:
+            logger.error(f"Failed to load state", exc_info=e)
+            return None
+
+    def save_state(self, state: ContestState):
+        logger.debug(f"Saving state")
+
+        with self._state_file.open("wb") as file:
+            file.write(state.model_dump_json(indent=4).encode())
diff --git a/validator/weight_setting/telemetry_attributes.py b/validator/weight_setting/telemetry_attributes.py
index 79d85a16..dec9b6c5 100644
--- a/validator/weight_setting/telemetry_attributes.py
+++ b/validator/weight_setting/telemetry_attributes.py
@@ -1,24 +1,23 @@
 import logging
+
 logging.disable()
 
-import sys
+from base.config import get_config
+from weight_setting.validator_args import add_args
 
 from fiber.chain.chain_utils import load_hotkey_keypair
 
-from neuron import get_config
-from weight_setting.validator import Validator
-
 
 def log_extra_attributes():
-    config = get_config(Validator.add_extra_args)
+    config = get_config(add_args)
 
     keypair = load_hotkey_keypair(
         wallet_name=config["wallet.name"],
         hotkey_name=config["wallet.hotkey"],
     )
 
-    sys.stdout.write(f"netuid={config['netuid']},neuron.hotkey={keypair.ss58_address}")
-    sys.stdout.flush()
+    print(f"netuid={config['netuid']},neuron.hotkey={keypair.ss58_address}")
+
 
 if __name__ == "__main__":
-    log_extra_attributes()
\ No newline at end of file
+    log_extra_attributes()
diff --git a/validator/weight_setting/validator.py b/validator/weight_setting/validator.py
index 47510df2..3a96b34c 100644
--- a/validator/weight_setting/validator.py
+++ b/validator/weight_setting/validator.py
@@ -1,864 +1,235 @@
-import random
-from argparse import ArgumentParser
-from dataclasses import dataclass
-from datetime import date, datetime, timedelta, time
-from json import JSONDecodeError
-from math import ceil
-from operator import itemgetter, attrgetter
-from os import makedirs
-from os.path import isfile
-from pathlib import Path
-from pickle import dump, load
-from ssl import SSLEOFError
-from time import sleep
+from datetime import timedelta
+from importlib.metadata import version
+from signal import signal, SIGINT, SIGHUP, SIGTERM
+from threading import Event
 from typing import Any
 
-import requests
-import wandb
-from opentelemetry import trace
-
-from base_validator import BenchmarkState, BenchmarkResults, AutoUpdater, init_open_telemetry_logging
 from fiber.chain.chain_utils import load_hotkey_keypair
 from fiber.chain.interface import get_substrate
 from fiber.chain.metagraph import Metagraph
-from fiber.chain.weights import set_node_weights
 from fiber.logging_utils import get_logger
-from substrateinterface.exceptions import SubstrateRequestException
+from opentelemetry import trace
+from requests.exceptions import HTTPError, ConnectionError
 from substrateinterface import SubstrateInterface, Keypair
-from wandb.sdk.wandb_run import Run
-
-from neuron import (
-    get_config,
-    CURRENT_CONTEST,
-    INPUTS_ENDPOINT,
-    Key,
-    Uid,
-    MinerModelInfo,
-    TIMEZONE,
-    SPEC_VERSION,
-    get_submissions,
-    BENCHMARKS_VERSION,
-    CheckpointBenchmark,
-    MetricData,
-)
-from neuron.device import ContestDeviceValidationError
-from .benchmarking_api import BenchmarkingApi, send_submissions_to_api
-from .wandb_args import add_wandb_args
-from .winner_selection import get_scores, get_contestant_scores, get_tiers, get_contestant_tier
-
-VALIDATOR_VERSION: tuple[int, int, int] = (5, 4, 0)
-VALIDATOR_VERSION_STRING = ".".join(map(str, VALIDATOR_VERSION))
-VALIDATOR_STATE_VERSION = 1
 
-WEIGHTS_VERSION = (
-    VALIDATOR_VERSION[0] * 10000 +
-    VALIDATOR_VERSION[1] * 100 +
-    VALIDATOR_VERSION[2]
-)
+from base.checkpoint import Uid
+from base.config import get_config
+from base.contest import BenchmarkState
+from base.submissions import get_submissions
+from base_validator.api_data import BenchmarkingResults
+from base_validator.auto_updater import AutoUpdater
+from base_validator.telemetry import init_open_telemetry_logging
+from weight_setting.wandb_manager import WandbManager
+from .benchmarking_api import BenchmarkingApi, send_submissions_to_api
+from .contest_state import ContestState
+from .state_manager import StateManager
+from .validator_args import add_args
+from .weight_setter import WeightSetter
 
-COLLECTED_SUBMISSIONS_VERSION = SPEC_VERSION * 10 + 2
+BENCHMARK_UPDATE_RATE_BLOCKS = 10
+BENCHMARKS_VERSION = 1
 
 logger = get_logger(__name__)
 tracer = trace.get_tracer(__name__)
 
 
-@dataclass
-class ContestState:
-    miner_score_version: int
-    submission_spec_version: int
-    miner_info: list[MinerModelInfo | None]
-
-    def __init__(
-        self,
-        miner_info: list[MinerModelInfo | None],
-    ):
-        self.miner_score_version = BENCHMARKS_VERSION
-        self.submission_spec_version = COLLECTED_SUBMISSIONS_VERSION
-        self.miner_info = miner_info
-
-
 class Validator:
-    auto_updater: AutoUpdater
-    config: dict[str, Any]
-    substrate: SubstrateInterface
-    metagraph: Metagraph
-    keypair: Keypair
+    _stop_flag: Event = Event()
+    auto_updater: AutoUpdater = AutoUpdater()
+    contest_state: ContestState | None = None
+    validator_version: str = version("edge-maxxing-validator")
     uid: Uid
 
-    hotkeys: list[Key]
-    step: int
+    config: dict[str, Any] = get_config(add_args)
 
-    last_day: date | None
-    contest_state: ContestState | None
-    benchmarking: bool
-    benchmarking_api_urls: list[str]
-    benchmarking_apis: list[BenchmarkingApi]
+    keypair: Keypair = load_hotkey_keypair(
+        wallet_name=config["wallet.name"],
+        hotkey_name=config["wallet.hotkey"],
+    )
 
-    wandb_run: Run | None
-    wandb_run_date: date | None
+    signature = f"0x{keypair.sign(f'{validator_version}:{keypair.ss58_address}').hex()}"
 
-    current_block: int
-    last_block_fetch: datetime | None = None
-    last_metagraph_sync: int = 0
-    attempted_set_weights: bool = False
+    substrate: SubstrateInterface = get_substrate(
+        subtensor_network=config["subtensor.network"],
+        subtensor_address=config["subtensor.chain_endpoint"]
+    )
 
-    benchmarks: list[CheckpointBenchmark | None]
-    last_benchmarks: list[CheckpointBenchmark | None]
-    baseline_metrics: MetricData | None
-    average_benchmarking_time: float | None
-    benchmarking_state: BenchmarkState
-    invalid: dict[int, str]
+    metagraph: Metagraph = Metagraph(
+        substrate=substrate,
+        netuid=config["netuid"],
+        load_old_nodes=False,
+    )
 
-    def __init__(self):
-        self.auto_updater = AutoUpdater()
-        self.config = get_config(Validator.add_extra_args)
-
-        logger.info(f"Validator version {VALIDATOR_VERSION_STRING}! Loading...")
+    state_manager: StateManager = StateManager(
+        wallet_name=config["wallet.name"],
+        hotkey_name=config["wallet.hotkey"],
+        netuid=metagraph.netuid,
+    )
 
-        self.substrate = get_substrate(
-            subtensor_network=self.config["subtensor.network"],
-            subtensor_address=self.config["subtensor.chain_endpoint"]
-        )
+    wandb_manager: WandbManager
 
-        self.metagraph = Metagraph(
-            self.substrate,
-
-            netuid=self.config["netuid"],
-            load_old_nodes=False,
-        )
+    weight_setter: WeightSetter
+    benchmarking_apis: list[BenchmarkingApi]
 
+    def __init__(self):
         self.metagraph.sync_nodes()
+        self.uid = list(self.metagraph.nodes.keys()).index(self.keypair.ss58_address)
 
-        self.keypair = load_hotkey_keypair(
-            wallet_name=self.config["wallet.name"],
-            hotkey_name=self.config["wallet.hotkey"],
-        )
-
-        self.hotkeys = list(self.metagraph.nodes.keys())
-
-        hotkey = self.keypair.ss58_address
-
-        self.uid = self.hotkeys.index(hotkey)
-        self.step = 0
-
-        signing_message = f"{VALIDATOR_VERSION_STRING}:{hotkey}"
-        signature = f"0x{self.keypair.sign(signing_message).hex()}"
         init_open_telemetry_logging({
             "neuron.uid": self.uid,
-            "neuron.signature": signature,
+            "neuron.signature": self.signature,
             "subtensor.chain_endpoint": self.substrate.url,
-            "validator.version": VALIDATOR_VERSION_STRING,
+            "validator.version": self.validator_version,
         })
 
-        self.last_day = None
-        self.contest_state = None
-        self.benchmarking = False
-        self.benchmarking_api_urls = self.config["benchmarker_api"]
-
-        self.wandb_run = None
-        self.wandb_run_date = None
-
-        self.benchmarks = self.clear_benchmarks()
-        self.last_benchmarks = self.clear_benchmarks()
-        self.baseline_metrics = None
-        self.average_benchmarking_time = None
-        self.benchmarking_state = BenchmarkState.NOT_STARTED
-        self.invalid = {}
-
-        self.load_state()
-        self.start_wandb_run()
-
-    def start_wandb_run(self):
-        if self.config["wandb.off"]:
-            return
-
-        if self.wandb_run:
-            logger.info("New contest day, starting a new wandb run.")
-            self.wandb_run.finish()
-
-        hotkey = self.keypair.ss58_address
-        day = self.last_day or self.current_time().date()
-        name = f"validator-{self.uid}-{day.year}-{day.month}-{day.day}"
-
-        contest_id = CURRENT_CONTEST.id
-
-        signing_message = f"{name}:{hotkey}:{contest_id.name}"
-        signature = f"0x{self.keypair.sign(signing_message).hex()}"
-
-        self.wandb_run = wandb.init(
-            name=name,
-            id=name,
-            resume="allow",
-            mode="offline" if self.config["wandb.offline"] else "online",
-            project=self.config["wandb.project_name"],
-            entity=self.config["wandb.entity"],
-            notes=self.config["wandb.notes"],
-            config={
-                "hotkey": hotkey,
-                "type": "validator",
-                "uid": self.uid,
-                "contest": contest_id.name,
-                "signature": signature,
-            },
-            allow_val_change=True,
-            anonymous="allow",
-            tags=[
-                f"version_{VALIDATOR_VERSION_STRING}",
-                f"sn{self.metagraph.netuid}",
-            ],
-        )
-
-        self.wandb_run_date = day
-        self.wandb_run.log(data={"benchmarking_state": self.benchmarking_state.name})
-
-        logger.debug(f"Started a new wandb run: {name}")
-
-    def send_wandb_metrics(self):
-        if not self.wandb_run:
-            return
-
-        submission_data = {
-            str(uid): {
-                "hotkey": self.hotkeys[uid],
-                "repository": info.repository.url,
-                "revision": info.repository.revision,
-                "block": info.block,
-            }
-            for uid, info in enumerate(self.contest_state.miner_info)
-            if info
-        }
-
-        log_data = {
-            "submissions": submission_data,
-            "benchmarks": self.get_wandb_benchmarks(self.benchmarks),
-            "last_benchmarks": self.get_wandb_benchmarks(self.last_benchmarks),
-            "invalid": self.invalid,
-            "benchmarking_state": self.benchmarking_state.name,
-        }
-
-        if self.average_benchmarking_time:
-            log_data["average_benchmark_time"] = self.average_benchmarking_time
-
-        if self.baseline_metrics:
-            log_data["baseline"] = self.baseline_metrics.model_dump()
-
-        self.wandb_run.log(data=log_data)
-
-        logger.info("Benchmarks uploaded to wandb")
-
-    def get_wandb_benchmarks(self, benchmarks: list[CheckpointBenchmark | None]):
-        benchmark_data = {}
-        tiers: list[list[Uid]] = []
-
-        if self.baseline_metrics:
-            contestants = get_contestant_scores(CURRENT_CONTEST, benchmarks, self.baseline_metrics)
-            tiers = get_tiers(contestants)
-
-        for uid, benchmark in enumerate(benchmarks):
-            if not benchmark:
-                continue
-
-            miner_info = self.contest_state.miner_info[uid]
-            if not miner_info:
-                continue
-
-            data = {
-               "similarity": benchmark.average_similarity,
-               "min_similarity": benchmark.min_similarity,
-            } | benchmark.model_dump()
-
-            if self.baseline_metrics:
-                data["score"] = CURRENT_CONTEST.calculate_score(self.baseline_metrics, benchmark)
-            if tiers:
-                data["tier"] = get_contestant_tier(tiers, uid)
-
-            benchmark_data[str(uid)] = data
-
-        return benchmark_data
-
-    @classmethod
-    def add_extra_args(cls, argument_parser: ArgumentParser):
-        argument_parser.add_argument(
-            "--epoch_length",
-            type=int,
-            help="The default epoch length (how often we pull the metagraph, measured in 12 second blocks).",
-            default=100,
-        )
-
-        argument_parser.add_argument(
-            "--benchmarker_api",
-            type=str,
-            nargs="*",
-            help="The API route to the validator benchmarking API.",
-            required=True,
-        )
-
-        argument_parser.add_argument(
-            "--delayed_weights.off",
-            action="store_true",
-            help="Turn off delayed weight setting.",
-            default=False,
+        self.wandb_manager = WandbManager(
+            config=self.config,
+            validator_version=self.validator_version,
+            uid=self.uid,
+            netuid=self.metagraph.netuid,
+            hotkey=self.keypair.ss58_address,
+            signature=self.signature,
         )
 
-        add_wandb_args(argument_parser)
-
-    @property
-    def state_path(self):
-        full_path = (
-            Path.home() /
-            ".bittensor" /
-            "miners" /
-            self.config["wallet.name"] /
-            self.config["wallet.hotkey"] /
-            f"netuid{self.metagraph.netuid}" /
-            "validator"
+        contest_state = self.state_manager.load_state()
+        if contest_state:
+            self.contest_state = contest_state
+            self.wandb_manager.init_wandb(self.contest_state)
+
+        self.weight_setter: WeightSetter = WeightSetter(
+            version=self.validator_version,
+            epoch_length=self.config["epoch_length"],
+            substrate=lambda: self.substrate,
+            metagraph=self.metagraph,
+            keypair=self.keypair,
+            uid=self.uid,
+            contest_state=lambda: self.contest_state,
         )
 
-        makedirs(full_path, exist_ok=True)
-
-        return full_path / f"state_{VALIDATOR_STATE_VERSION}.bin"
-
-    def save_state(self):
-        """Saves the state of the validator to a file."""
-        logger.info("Saving validator state.")
-
-        # Save the state of the validator to file.
-        with open(self.state_path, "wb") as file:
-            dump(
-                {
-                    "step": self.step,
-                    "hotkeys": self.hotkeys,
-                    "benchmarks": self.benchmarks,
-                    "last_benchmarks": self.last_benchmarks,
-                    "baseline_benchmarks": self.baseline_metrics,
-                    "average_benchmarking_time": self.average_benchmarking_time,
-                    "benchmarking_state": self.benchmarking_state,
-                    "invalid": self.invalid,
-                    "last_day": self.last_day,
-                    "contest_state": self.contest_state,
-                    "benchmarking": self.benchmarking,
-                    "last_metagraph_sync": self.last_metagraph_sync,
-                },
-                file,
-            )
+        self.benchmarking_apis = [BenchmarkingApi(api=api, keypair=self.keypair) for api in self.config["benchmarker_api"]]
 
-    def load_state(self):
-        """Loads the state of the validator from a file."""
-        path = self.state_path
-
-        if not isfile(path):
-            return
+        self.run()
 
-        logger.info("Loading validator state.")
-
-        # Load the state of the validator from file.
-        with open(path, "rb") as file:
-            state = load(file)
-
-        self.step = state["step"]
-        self.hotkeys = state["hotkeys"]
-        self.benchmarks = state.get("benchmarks", self.benchmarks)
-        self.last_benchmarks = state.get("last_benchmarks", self.last_benchmarks)
-        self.baseline_metrics = state.get("baseline_benchmarks", self.baseline_metrics)
-        self.average_benchmarking_time = state.get("average_benchmarking_time", self.average_benchmarking_time)
-        self.benchmarking_state = state.get("benchmarking_state", self.benchmarking_state)
-        self.invalid = state.get("invalid", self.invalid)
-        self.last_day = state["last_day"]
-        self.contest_state = state["contest_state"]
-        self.benchmarking = state.get("benchmarking", self.benchmarking)
-        self.last_metagraph_sync = state.get("last_metagraph_sync", self.last_metagraph_sync)
-
-        if self.contest_state:
-            if self.contest_state.miner_score_version != BENCHMARKS_VERSION:
-                logger.warning(
-                    f"Contest state has outdated weights version: {self.contest_state.miner_score_version}, "
-                    f"current version: {BENCHMARKS_VERSION}. Resetting benchmarks."
-                )
-
-                self.benchmarks = self.clear_benchmarks()
-                self.invalid.clear()
-                self.contest_state.miner_score_version = BENCHMARKS_VERSION
-
-            if self.contest_state.submission_spec_version != COLLECTED_SUBMISSIONS_VERSION:
-                logger.warning(
-                    f"Contest state has outdated spec version: {self.contest_state.submission_spec_version}, "
-                    f"current version: {COLLECTED_SUBMISSIONS_VERSION}. Resetting benchmarks."
-                )
-
-                self.benchmarks = self.clear_benchmarks()
-                self.invalid.clear()
-
-                self.benchmarking = True
-                self.contest_state.miner_info = self.get_miner_submissions()
-                self.contest_state.submission_spec_version = COLLECTED_SUBMISSIONS_VERSION
-
-    def clear_benchmarks(self) -> list[CheckpointBenchmark | None]:
-        return [None] * len(self.metagraph.nodes)
-
-    def reset_miner(self, uid: Uid):
-        self.benchmarks[uid] = None
-        self.last_benchmarks[uid] = None
-
-        if uid in self.invalid:
-            del self.invalid[uid]
-
-    def resize(self):
-        new_data = self.clear_benchmarks()
-        length = len(self.metagraph.nodes)
-        new_data[:length] = self.benchmarks[:length]
-        self.benchmarks = new_data
-
-    def check_registration(self):
-        hotkey = self.keypair.ss58_address
-        if hotkey not in self.hotkeys:
-            logger.error(
-                f"Wallet: {self.keypair} is not registered on netuid {self.metagraph.netuid}."
+    @tracer.start_as_current_span("initialize_contest")
+    def initialize_contest(self):
+        self.contest_state.benchmarking_state = BenchmarkState.NOT_STARTED
+        for api in self.benchmarking_apis:
+            api.initialize(
+                uid=self.uid,
+                signature=self.signature,
+                substrate_url=self.substrate.url,
             )
 
-    def metagraph_nodes(self):
-        return sorted(self.metagraph.nodes.values(), key=attrgetter("node_id"))
-
-    def sync_chain_nodes(self, block: int):
-        logger.info("Syncing metagraph")
-
         self.metagraph.sync_nodes()
-
-        self.check_registration()
-
-        if len(self.hotkeys) != len(self.metagraph.nodes):
-            self.resize()
-
-            if self.contest_state:
-                new_miner_info = [None] * len(self.metagraph.nodes)
-                length = len(self.hotkeys)
-                new_miner_info[:length] = self.contest_state.miner_info[:length]
-
-                self.contest_state.miner_info = new_miner_info
-
-        nodes = self.metagraph_nodes()
-
-        for uid, hotkey in enumerate(self.hotkeys):
-            if hotkey != nodes[uid].hotkey:
-                # hotkey has been replaced
-                self.reset_miner(uid)
-
-                if self.contest_state:
-                    self.contest_state.miner_info[uid] = None
-
-        self.hotkeys = list(self.metagraph.nodes.keys())
-        self.last_metagraph_sync = block
-
-    def sync(self, block: int):
-        if block - self.last_metagraph_sync > self.config["epoch_length"]:
-            self.sync_chain_nodes(block)
-
-        try:
-            self.set_weights()
-
-            self.attempted_set_weights = True
-
-            self.sync_chain_nodes(block)
-        except SubstrateRequestException as e:
-            logger.error(f"Failed to set weights: {e}")
-        except Exception as e:
-            logger.error(f"Failed to set weights", exc_info=e)
-
-    @tracer.start_as_current_span("set_weights")
-    def set_weights(self):
-        if self.attempted_set_weights:
-            return
-
-        equal_weights = False
-        delayed_weights = not self.config["delayed_weights.off"]
-        benchmarks = self.last_benchmarks if delayed_weights else self.benchmarks
-
-        if not delayed_weights and self.benchmarking:
-            logger.info("Not setting new weights as benchmarking is not done, reusing old weights")
-            delayed_weights = True
-            benchmarks = self.last_benchmarks
-
-        if not self.contest_state:
-            logger.info("Will not set new weights as the contest state has not been set, setting to all ones")
-            equal_weights = True
-
-        elif not self.baseline_metrics:
-            logger.info("Will not set new weights as the baseline benchmarks have not been set, setting to all ones")
-            equal_weights = True
-
-        elif all(benchmark is None for benchmark in self.last_benchmarks):
-            if any(benchmark is not None for benchmark in self.benchmarks):
-                logger.info("Setting weights to current benchmarks as the previous day's benchmarks have not been set")
-                self.last_benchmarks = self.benchmarks
-            elif delayed_weights:
-                logger.info("Will not set new weights as the previous day's benchmarks have not been set, setting to all ones")
-                equal_weights = True
-
-        if equal_weights:
-            uids = list(range(len(self.metagraph.nodes)))
-            weights = [1.0] * len(self.metagraph.nodes)
-
-            set_node_weights(
-                self.substrate,
-                self.keypair,
-                node_ids=list(uids),
-                node_weights=list(weights),
-                netuid=self.metagraph.netuid,
-                validator_node_id=self.uid,
-                version_key=WEIGHTS_VERSION,
+        self.contest_state.start_new_contest(
+            benchmarks_version=BENCHMARKS_VERSION,
+            submissions=get_submissions(
+                substrate=self.substrate,
+                metagraph=self.metagraph,
+                block=self.substrate.get_block_number(None),  # type: ignore
             )
-
-            return
-
-        logger.info("Setting weights")
-
-        blacklisted_keys = self.get_blacklisted_keys()
-        for hotkey, node in self.metagraph.nodes.items():
-            uid = self.hotkeys.index(hotkey)
-            if benchmarks[uid]:
-                if self.is_blacklisted(blacklisted_keys, hotkey, node.coldkey):
-                    logger.warning(f"Not setting weights for blacklisted hotkey {hotkey}")
-                    self.reset_miner(uid)
-                elif not self.contest_state.miner_info[uid]:
-                    logger.warning(f"Not setting weights for hotkey {hotkey} as their submission was not found")
-                    self.reset_miner(uid)
-
-        contestants = get_contestant_scores(CURRENT_CONTEST, benchmarks, self.baseline_metrics)
-        tiers = get_tiers(contestants)
-        blocks = [info.block if info else None for info in self.contest_state.miner_info]
-        weights = get_scores(tiers, blocks, len(self.metagraph.nodes))
-
-        self.send_wandb_metrics()
-
-        if sum(weights) <= 0.0:
-            weights = [1.0] * len(self.metagraph.nodes)
-
-        set_node_weights(
-            self.substrate,
-            self.keypair,
-            node_ids=list(range(len(self.metagraph.nodes))),
-            node_weights=weights,
-            netuid=self.metagraph.netuid,
-            validator_node_id=self.uid,
-            version_key=WEIGHTS_VERSION,
-        )
-
-        self.metagraph.sync_nodes()
-
-    @staticmethod
-    def get_blacklisted_keys():
-        response = requests.get(
-            f"{INPUTS_ENDPOINT}/blacklist", headers={
-                "Content-Type": "application/json"
-            },
-        )
-
-        response.raise_for_status()
-        return response.json()
-
-    @staticmethod
-    def is_blacklisted(blacklisted_keys: dict, hotkey: str, coldkey: str):
-        return hotkey in blacklisted_keys["hotkeys"] or coldkey in blacklisted_keys["coldkeys"]
-
-    @tracer.start_as_current_span("get_miner_submissions")
-    def get_miner_submissions(self) -> list[MinerModelInfo | None]:
-        blacklisted_keys = self.get_blacklisted_keys()
-
-        hotkeys = [
-            hotkey
-            for hotkey, node in self.metagraph.nodes.items()
-            if not self.is_blacklisted(blacklisted_keys, hotkey, node.coldkey)
-        ]
-
-        return get_submissions(
-            substrate=self.substrate,
-            hotkeys=hotkeys,
-            netuid=self.metagraph.netuid,
-            block=self.block,
         )
 
-    def start_benchmarking(self, submissions: dict[Key, MinerModelInfo]):
-        return send_submissions_to_api(self.benchmarking_apis, submissions)
-
-    @staticmethod
-    def current_time():
-        return datetime.now(tz=TIMEZONE)
-
-    def non_tested_miners(self) -> list[Uid]:
-        return list(
-            {
-                uid
-                for uid, miner_info in enumerate(self.contest_state.miner_info)
-                if miner_info and not self.benchmarks[uid] and uid not in self.invalid
-            }
-        )
-
-    @tracer.start_as_current_span("initialize_contest")
-    def initialize_contest(self, now: datetime):
-        logger.info("Collecting all submissions")
-
-        miner_info = self.get_miner_submissions()
-
-        logger.info(f"Got {len([info for info in miner_info if info])} submissions")
-
-        logger.info(f"Working on contest {CURRENT_CONTEST.id.name}")
-
-        if not self.contest_state:
-            self.contest_state = ContestState(miner_info)
-        else:
-            self.contest_state.miner_info = miner_info
-
-        self.average_benchmarking_time = None
-        self.benchmarking_state = BenchmarkState.NOT_STARTED
-
-        logger.info(f"Setting updated benchmarks")
-        self.last_benchmarks = self.benchmarks
-
-        self.benchmarks = self.clear_benchmarks()
-        self.invalid.clear()
-
-        self.last_day = now.date()
-
-        self.start_wandb_run()
-
-        self.benchmarking = False
+        if not self.contest_state.submissions:
+            sleep_blocks = self.config["epoch_length"]
+            logger.warning(f"No submissions found, sleeping for {sleep_blocks} blocks")
+            self._stop_flag.wait(sleep_blocks * 12)
+            return
 
-        self.step += 1
+        self.wandb_manager.init_wandb(self.contest_state)
+        logger.info(f"Starting a new contest with {len(self.contest_state.submissions)} submissions")
 
     @tracer.start_as_current_span("do_step")
-    def do_step(self, block: int):
-        now = self.current_time()
+    def do_step(self):
+        if not self.contest_state:
+            self.contest_state = ContestState.create(BENCHMARKS_VERSION)
 
-        if (not self.last_day or self.last_day < now.date()) and now.hour >= 12:
-            # Past noon, should start collecting submissions
-            self.initialize_contest(now)
+        if self.contest_state.is_ended() or self.contest_state.benchmarks_version != BENCHMARKS_VERSION:
+            self.initialize_contest()
             return
 
-        last_update = self.metagraph.nodes[self.keypair.ss58_address].last_updated
-        blocks_elapsed = block - last_update
-        epoch_length = self.config["epoch_length"]
-
-        if blocks_elapsed >= epoch_length:
-            logger.info(f"{blocks_elapsed} blocks since weight setting, attempting to set weights")
-            self.sync(block)
-
-            # Recalculate in-case weights were set
-            blocks_elapsed = block - self.metagraph.nodes[self.keypair.ss58_address].last_updated
-        else:
-            logger.info(
-                f"{blocks_elapsed} since last update, "
-                f"{epoch_length - blocks_elapsed} blocks remaining until weight setting"
-            )
-
-        if not self.benchmarking:
-            self.step += 1
-
-            if self.contest_state:
-                remaining = self.non_tested_miners()
-
-                if remaining:
-                    nodes = self.metagraph_nodes()
-
-                    submissions = {
-                        nodes[uid].hotkey: self.contest_state.miner_info[uid]
-                        for uid in remaining
-                    }
-
-                    try:
-                        self.start_benchmarking(submissions)
-                    except Exception as e:
-                        logger.error(f"Failed to start benchmarking, retrying in 60 seconds", exc_info=e)
-                        sleep(60)
-                        return
-
-                    self.benchmarking = True
-
-                    self.save_state()
-
-                    return
-
-            blocks_to_wait = epoch_length - blocks_elapsed
-
-            if blocks_to_wait <= 0:
-                # Randomize in case multiple validators are in this same state,
-                # to avoid multiple validators setting weights all in the same block
-                blocks_to_wait = random.randint(1, 10)
-
-            self.sleep_for_blocks(now, blocks_to_wait, "Nothing to do in this step")
+        untested_submissions = self.contest_state.get_untested_submissions()
 
+        if not untested_submissions:
+            self.contest_state.benchmarking_state = BenchmarkState.FINISHED
+            self.wandb_manager.send_metrics(self.contest_state)
+            self.contest_state.sleep_to_next_contest(self._stop_flag)
             return
 
-        try:
-            states: list[BenchmarkResults] = [api.state() for api in self.benchmarking_apis]
-        except Exception as e:
-            logger.error(f"Failed to get benchmarking states, retrying in 60 seconds", exc_info=e)
-            sleep(60)
-            return
-
-        not_started = []
-        in_progress = []
-        finished = []
-
-        for index, result in enumerate(states):
-            match result.state:
-                case BenchmarkState.NOT_STARTED:
-                    not_started.append((index, result))
-                case BenchmarkState.IN_PROGRESS:
-                    in_progress.append((index, result))
-                case BenchmarkState.FINISHED:
-                    finished.append((index, result))
-
-            if result.baseline_metrics and self.baseline_metrics != result.baseline_metrics:
-                self.baseline_metrics = result.baseline_metrics
-                logger.info(f"Updated baseline benchmarks to {result.baseline_metrics}")
-
-        self.benchmarking_state = min((result.state for result in states), key=lambda state: state.value)
+        benchmarking_results = [api.results() for api in self.benchmarking_apis]
 
-        with_results = in_progress + finished
-
-        if not_started:
-            api_indices = list(map(itemgetter(0), not_started))
-
-            api_names = ",".join(
-                str(index + 1)
-                for index in api_indices
+        if any(result.state == BenchmarkState.NOT_STARTED for result in benchmarking_results):
+            send_submissions_to_api(
+                version=self.validator_version,
+                all_apis=self.benchmarking_apis,
+                submissions=untested_submissions,
             )
+            return
 
-            # API likely crashed or got restarted, need to re-benchmark any submissions sent to API
-            logger.info(
-                f"APIs {api_names} are in a different state than expected, likely restarted. "
-                "Sending submissions again for testing"
-            )
-
-            nodes = self.metagraph_nodes()
-
-            submissions = {
-                nodes[uid].hotkey: self.contest_state.miner_info[uid]
-                for uid in self.non_tested_miners()
-            }
-
-            apis = [
-                self.benchmarking_apis[index]
-                for index in api_indices
-            ]
-
-            try:
-                send_submissions_to_api(apis, submissions)
-            except Exception as e:
-                logger.error(f"Failed to restart benchmarking, retrying in 60 seconds", exc_info=e)
-                sleep(60)
-                return
-
-            if not with_results:
-                self.step += 1
-                self.save_state()
-
-                return
-
-        benchmark_times = [
-            result.average_benchmark_time
-            for _, result in with_results
-            if result.average_benchmark_time
-        ]
-
-        for _, result in with_results:
-            def get_uid(hotkey: Key) -> Uid | None:
-                if not hotkey in self.hotkeys:
-                    logger.info(f"{hotkey} not found, skipping")
-                    return None
-
-                uid = self.hotkeys.index(hotkey)
-
-                if not self.contest_state.miner_info[uid]:
-                    logger.info(f"{hotkey} has no submission, skipping")
-                    return None
-
-                return uid
-
-
-            for hotkey, benchmark in result.results.items():
-                uid = get_uid(hotkey)
-                if uid is None:
-                    continue
-
-                if benchmark and self.benchmarks[uid] != benchmark:
-                    logger.info(f"Updating {hotkey}'s benchmarks to {benchmark}")
-                self.benchmarks[uid] = benchmark
-
-            for hotkey, error_message in result.invalid.items():
-                uid = get_uid(hotkey)
-                if uid is None:
-                    continue
-
-                if error_message and error_message != self.invalid.get(uid):
-                    logger.info(f"Marking {hotkey}'s submission as invalid: '{error_message}'")
-                self.invalid[uid] = error_message
+        self.update_benchmarks(benchmarking_results)
+        self.contest_state.benchmarking_state = BenchmarkState.IN_PROGRESS
+        self._stop_flag.wait(BENCHMARK_UPDATE_RATE_BLOCKS * 12)
 
-        self.average_benchmarking_time = (sum(benchmark_times) / len(benchmark_times)) if benchmark_times else None
-        self.send_wandb_metrics()
+    def update_benchmarks(self, benchmarking_results: list[BenchmarkingResults]):
+        if not self.contest_state:
+            return
 
-        if not not_started and not in_progress and finished:
-            logger.info("Benchmarking APIs have reported submission testing as done.")
+        baseline = benchmarking_results[0].baseline
+        average_benchmarking_time = benchmarking_results[0].average_benchmarking_time
 
-            self.benchmarking = False
-            self.step += 1
+        if baseline and baseline != self.contest_state.baseline:
+            logger.info(f"Updating baseline to {baseline}")
 
-            self.save_state()
-            return
+        self.contest_state.baseline = baseline
 
-        self.step += 1
+        for result in benchmarking_results:
+            for key in result.benchmarks.keys() - self.contest_state.benchmarks.keys():
+                logger.info(f"Updating benchmarks for {key}")
+            for key in result.invalid_submissions - self.contest_state.invalid_submissions:
+                logger.info(f"Marking submission from {key} as invalid")
 
-        self.save_state()
+            self.contest_state.benchmarks.update(result.benchmarks)
+            self.contest_state.invalid_submissions.update(result.invalid_submissions)
 
-        self.sleep_for_blocks(now, epoch_length / 4, "Benchmarking in progress")
+        if average_benchmarking_time and average_benchmarking_time != self.contest_state.average_benchmarking_time:
+            benchmarked = len(self.contest_state.benchmarks) + len(self.contest_state.invalid_submissions)
+            eta = (len(self.contest_state.submissions) - benchmarked) * average_benchmarking_time
+            logger.info(f"{benchmarked}/{len(self.contest_state.submissions)} benchmarked. Average benchmark time: {average_benchmarking_time:.2f}s, ETA: {timedelta(seconds=int(eta))}")
 
-    @tracer.start_as_current_span("sleep_for_blocks")
-    def sleep_for_blocks(self, now: datetime, blocks: int, reason: str):
-        next_noon = datetime.combine(now.date() + timedelta(days=int(now.hour >= 12)), time(12), tzinfo=TIMEZONE)
-        blocks_to_sleep = min(blocks, ceil((next_noon - now).total_seconds() / 12))
-        logger.info(f"{reason}, sleeping for {blocks_to_sleep} blocks")
-        sleep(blocks_to_sleep * 12)
+        self.contest_state.average_benchmarking_time = average_benchmarking_time
 
-    @property
-    def block(self):
-        if not self.last_block_fetch or (datetime.now() - self.last_block_fetch).seconds >= 12:
-            self.current_block = self.substrate.get_block_number(None)  # type: ignore
-            self.last_block_fetch = datetime.now()
-            self.attempted_set_weights = False
+    def step(self):
+        return self.contest_state.step if self.contest_state else 0
 
-        return self.current_block
+    def _shutdown(self, _signalnum, _handler):
+        logger.info("Shutting down validator")
+        self.weight_setter.shutdown()
+        self.auto_updater.shutdown()
+        self._stop_flag.set()
 
     def run(self):
-        self.benchmarking_apis = [
-            BenchmarkingApi(self.keypair, api)
-            for api in self.benchmarking_api_urls
-        ]
-
-        while True:
+        logger.info("Initializing validator")
+        signal(SIGTERM, self._shutdown)
+        signal(SIGINT, self._shutdown)
+        signal(SIGHUP, self._shutdown)
+        while not self._stop_flag.is_set():
             try:
-                current_block = self.block
-
-                logger.info(f"Step {self.step}, block {current_block}")
-
-                self.do_step(current_block)
-            except KeyboardInterrupt:
-                logger.info("Shutting down validator")
-                break
+                logger.info(f"Step {self.step()}")
+                self.do_step()
+                if self.contest_state:
+                    self.contest_state.step += 1
+                    self.state_manager.save_state(self.contest_state)
+                    self.wandb_manager.send_metrics(self.contest_state)
+            except (ConnectionError, HTTPError) as e:
+                logger.error(f"Error connecting to API, retrying in 10 blocks: {e}")
+                self._stop_flag.wait(BENCHMARK_UPDATE_RATE_BLOCKS * 12)
             except Exception as e:
-                if not isinstance(e, ContestDeviceValidationError):
-                    if isinstance(e, (SSLEOFError, JSONDecodeError)):
-                        logger.error(f"Error during validation step {self.step}: {e}")
-                    else:
-                        logger.error(f"Error during validation step {self.step}", exc_info=e)
-
-                    self.substrate = get_substrate(subtensor_address=self.substrate.url)
-
-                    continue
-
-                raise
+                logger.error(f"Error during step {self.step()}", exc_info=e)
+                self.substrate = get_substrate(subtensor_address=self.substrate.url)
 
 
 def main():
-    Validator().run()
+    Validator()
 
 
 if __name__ == '__main__':
diff --git a/validator/weight_setting/validator_args.py b/validator/weight_setting/validator_args.py
new file mode 100644
index 00000000..d5c8df85
--- /dev/null
+++ b/validator/weight_setting/validator_args.py
@@ -0,0 +1,22 @@
+from argparse import ArgumentParser
+
+from .wandb_manager import add_wandb_args
+
+
+def add_args(argument_parser: ArgumentParser):
+    argument_parser.add_argument(
+        "--epoch_length",
+        type=int,
+        help="The default epoch length (how often we pull the metagraph, measured in 12 second blocks).",
+        default=100,
+    )
+
+    argument_parser.add_argument(
+        "--benchmarker_api",
+        type=str,
+        nargs="*",
+        help="The API route to the validator benchmarking API.",
+        required=True,
+    )
+
+    add_wandb_args(argument_parser)
diff --git a/validator/weight_setting/wandb_args.py b/validator/weight_setting/wandb_args.py
deleted file mode 100644
index 636185f5..00000000
--- a/validator/weight_setting/wandb_args.py
+++ /dev/null
@@ -1,38 +0,0 @@
-from argparse import ArgumentParser
-
-
-def add_wandb_args(parser: ArgumentParser):
-    parser.add_argument(
-        "--wandb.off",
-        action="store_true",
-        help="Turn off wandb.",
-        default=False,
-    )
-
-    parser.add_argument(
-        "--wandb.offline",
-        action="store_true",
-        help="Runs wandb in offline mode.",
-        default=False,
-    )
-
-    parser.add_argument(
-        "--wandb.notes",
-        type=str,
-        help="Notes to add to the wandb run.",
-        default="",
-    )
-
-    parser.add_argument(
-        "--wandb.entity",
-        type=str,
-        help="Wandb entity to log to.",
-        default="w-ai-wombo",
-    )
-
-    parser.add_argument(
-        "--wandb.project_name",
-        type=str,
-        help="The name of the project where you are sending the new run.",
-        default="edge-maxxing",
-    )
diff --git a/validator/weight_setting/wandb_manager.py b/validator/weight_setting/wandb_manager.py
new file mode 100644
index 00000000..0219ae0f
--- /dev/null
+++ b/validator/weight_setting/wandb_manager.py
@@ -0,0 +1,116 @@
+from argparse import ArgumentParser
+from typing import Any
+
+import wandb
+from wandb.apis.public import Run
+
+from base.checkpoint import Uid
+from .contest_state import ContestState
+
+
+class WandbManager:
+    _run: Run | None = None
+
+    config: dict[str, Any]
+    validator_version: str
+    uid: Uid
+    netuid: Uid
+    hotkey: str
+    signature: str
+
+    def __init__(
+        self,
+        config: dict[str, Any],
+        validator_version: str,
+        uid: Uid,
+        netuid: Uid,
+        hotkey: str,
+        signature: str,
+    ):
+        self.config = config
+        self.validator_version = validator_version
+        self.uid = uid
+        self.netuid = netuid
+        self.hotkey = hotkey
+        self.signature = signature
+
+    def init_wandb(self, contest_state: ContestState):
+        if self.config["wandb.off"]:
+            return
+
+        if self._run:
+            self._run.finish()
+
+        day = contest_state.get_contest_start()
+        name = f"validator-{self.uid}-{day.year}-{day.month}-{day.day}"
+
+        self._run = wandb.init(
+            name=name,
+            id=name,
+            resume="allow",
+            mode="offline" if self.config["wandb.offline"] else "online",
+            project=self.config["wandb.project_name"],
+            entity=self.config["wandb.entity"],
+            notes=self.config["wandb.notes"],
+            config={
+                "hotkey": self.hotkey,
+                "type": "validator",
+                "uid": self.uid,
+                "signature": self.signature,
+            },
+            allow_val_change=True,
+            anonymous="allow",
+            tags=[
+                f"version_{self.validator_version}",
+                f"sn{self.netuid}",
+            ],
+        )
+
+    def send_metrics(self, contest_state: ContestState):
+        if not self._run or self.config["wandb.off"]:
+            return
+
+        scores = contest_state.get_scores()
+        data = {
+            "scores": scores,
+            "ranks": contest_state.get_ranks(scores),
+        } | contest_state.model_dump()
+
+        self._run.log(data=data)
+
+
+def add_wandb_args(parser: ArgumentParser):
+    parser.add_argument(
+        "--wandb.off",
+        action="store_true",
+        help="Turn off wandb.",
+        default=False,
+    )
+
+    parser.add_argument(
+        "--wandb.offline",
+        action="store_true",
+        help="Runs wandb in offline mode.",
+        default=False,
+    )
+
+    parser.add_argument(
+        "--wandb.notes",
+        type=str,
+        help="Notes to add to the wandb run.",
+        default="",
+    )
+
+    parser.add_argument(
+        "--wandb.entity",
+        type=str,
+        help="Wandb entity to log to.",
+        default="w-ai-wombo",
+    )
+
+    parser.add_argument(
+        "--wandb.project_name",
+        type=str,
+        help="The name of the project where you are sending the new run.",
+        default="edge-maxxing",
+    )
diff --git a/validator/weight_setting/weight_setter.py b/validator/weight_setting/weight_setter.py
new file mode 100644
index 00000000..7a6b0d84
--- /dev/null
+++ b/validator/weight_setting/weight_setter.py
@@ -0,0 +1,121 @@
+from random import randint
+from threading import Thread, Event
+from typing import Callable
+
+from fiber.chain.metagraph import Metagraph
+from fiber.chain.weights import set_node_weights
+from fiber.logging_utils import get_logger
+from opentelemetry import trace
+from substrateinterface import SubstrateInterface, Keypair
+
+from base.inputs_api import blacklisted_keys, is_blacklisted
+from weight_setting.contest_state import ContestState
+
+logger = get_logger(__name__)
+tracer = trace.get_tracer(__name__)
+
+
+class WeightSetter:
+    _thread: Thread
+    _stop_flag: Event = Event()
+
+    _epoch_length: int
+    _substrate: Callable[[], SubstrateInterface]
+    _metagraph: Metagraph
+    _keypair: Keypair
+    _uid: int
+    _contest_state: Callable[[], ContestState]
+    _weights_version: int
+
+    def __init__(
+        self,
+        version: str,
+        epoch_length: int,
+        substrate: Callable[[], SubstrateInterface],
+        metagraph: Metagraph,
+        keypair: Keypair,
+        uid: int,
+        contest_state: Callable[[], ContestState],
+    ):
+        self._epoch_length = epoch_length
+        self._substrate = substrate
+        self._metagraph = metagraph
+        self._keypair = keypair
+        self._uid = uid
+        self._contest_state = contest_state
+
+        parts: list[str] = version.split(".")
+        self._weights_version = int(parts[0]) * 10000 + int(parts[1]) * 100 + int(parts[2])
+
+        self._thread = Thread(target=self._run)
+        self._thread.start()
+
+    def shutdown(self):
+        self._stop_flag.set()
+
+    def _run(self):
+        while not self._stop_flag.is_set():
+            try:
+                if self.set_weights():
+                    logger.info(f"Successfully set weights, sleeping for {self._epoch_length} blocks")
+                    self._stop_flag.wait(self._epoch_length * 12)
+                else:
+                    raise RuntimeError("Set weights attempt was unsuccessful")
+            except Exception as e:
+                blocks_to_sleep = randint(10, 50)
+                logger.error(f"Failed to set weights, retrying in {blocks_to_sleep} blocks: {e}")
+                self._stop_flag.wait(blocks_to_sleep * 12)
+
+    @tracer.start_as_current_span("set_weights")
+    def set_weights(self) -> bool:
+        contest_state = self._contest_state()
+
+        if not contest_state:
+            logger.warning("Will not set new weights as the contest state has not been set, setting to all ones")
+            return self._set_equal_weights()
+
+        benchmarks = contest_state.last_benchmarks
+
+        if not contest_state.baseline:
+            logger.warning("Will not set new weights as the baseline benchmarks have not been set, setting to all ones")
+            return self._set_equal_weights()
+
+        if not contest_state.last_benchmarks:
+            if contest_state.benchmarks:
+                logger.info("Setting weights to current benchmarks as the previous day's benchmarks have not been set")
+                benchmarks = contest_state.benchmarks
+            else:
+                logger.warning("Will not set new weights as the previous day's benchmarks have not been set, setting to all ones")
+                return self._set_equal_weights()
+
+        self._metagraph.sync_nodes()
+        blacklist = blacklisted_keys()
+        for hotkey, node in self._metagraph.nodes.items():
+            if is_blacklisted(blacklist, hotkey, node.coldkey):
+                benchmarks.pop(hotkey, None)
+            if not hotkey in contest_state.submissions:
+                benchmarks.pop(hotkey, None)
+
+        scores = contest_state.get_scores()
+        ranks = contest_state.get_ranks(scores)
+
+        weights_by_key = contest_state.calculate_weights(ranks=ranks)
+
+        return self._set_weights([
+            weights_by_key.get(key, 0)
+            for key in self._metagraph.nodes.keys()
+        ])
+
+    def _set_equal_weights(self) -> bool:
+        return self._set_weights([1.0] * len(self._metagraph.nodes))
+
+    def _set_weights(self, weights: list[float]) -> bool:
+        return set_node_weights(
+            self._substrate(),
+            self._keypair,
+            node_ids=list(range(len(self._metagraph.nodes))),
+            node_weights=weights,
+            netuid=self._metagraph.netuid,
+            validator_node_id=self._uid,
+            version_key=self._weights_version,
+        )
diff --git a/validator/weight_setting/winner_selection.py b/validator/weight_setting/winner_selection.py
index 6b9e5a5b..5dd0d618 100644
--- a/validator/weight_setting/winner_selection.py
+++ b/validator/weight_setting/winner_selection.py
@@ -1,83 +1,72 @@
 from operator import itemgetter
 
-from neuron import Uid, Contest
-from neuron.submission_tester import CheckpointBenchmark, MetricData
+from base.checkpoint import Key, Submissions, Benchmarks
+from base.contest import Metrics
 
-TIER_SCORE_IMPROVEMENT_THRESHOLD = 1.05
+RANK_SCORE_IMPROVEMENT_THRESHOLD = 1.05
 WINNER_PERCENTAGE = 0.80
 
 
-def get_contestant_scores(contest: Contest, benchmarks: list[CheckpointBenchmark | None], baseline_metrics: MetricData) -> list[tuple[Uid, float]]:
-    contestants = [
-        (uid, contest.calculate_score(baseline_metrics, benchmark))
-        for uid, benchmark in enumerate(benchmarks)
-        if benchmark
-    ]
+def get_contestant_scores(
+    submissions: Submissions,
+    benchmarks: Benchmarks,
+    baseline: Metrics,
+) -> dict[Key, float]:
+    return {
+        key: submissions[key].contest().calculate_score(baseline, benchmark)
+        for key, benchmark in benchmarks.items()
+    }
 
-    sorted_contestants = sorted(contestants, key=itemgetter(1), reverse=True)
 
-    return sorted_contestants
+def get_contestant_ranks(scores: dict[Key, float]) -> dict[Key, int]:
+    if not scores:
+        return {}
 
+    scores = iter(sorted(scores.items(), key=itemgetter(1), reverse=True))
 
-def get_tiers(contestants: list[tuple[Uid, float]]) -> list[list[Uid]]:
-    if not contestants:
-        return []
+    hotkey, last_score = next(scores)
 
-    _, last_tier_score = contestants[0]
+    rank = 0
+    ranks = {hotkey: rank}
 
-    tiers = [[]]
+    for hotkey, score in scores:
+        if last_score > score * RANK_SCORE_IMPROVEMENT_THRESHOLD:
+            last_score = score
+            rank += 1
 
-    for contestant in contestants:
-        uid, score = contestant
+        ranks[hotkey] = rank
 
-        if last_tier_score > score * TIER_SCORE_IMPROVEMENT_THRESHOLD:
-            # New tier
-            last_tier_score = score
-            tiers.append([])
+    return ranks
 
-        tiers[-1].append(uid)
 
-    return list(reversed(tiers))
+def calculate_rank_weights(
+    submitted_blocks: dict[Key, int],
+    ranks: dict[Key, int],
+) -> dict[Key, float]:
+    if not ranks:
+        return {}
 
+    ranks = iter(sorted(ranks.items(), key=lambda rank: (rank[1], submitted_blocks[rank[0]])))
 
-def get_contestant_tier(tiers: list[list[Uid]], uid: Uid) -> int:
-    for index, tier in enumerate(tiers):
-        if uid in tier:
-            return index
+    last_rank = None
 
-    return -1
+    rank_hotkeys = [[]]
 
+    for hotkey, rank in ranks:
+        rank_hotkeys[-1].append(hotkey)
 
-def get_scores(tiers: list[list[Uid]], blocks: list[int | None], node_count: int) -> list[float]:
-    if not tiers:
-        return [1.0] * node_count
+        if rank != last_rank:
+            rank_hotkeys.append([])
 
-    ordered_tiers = [
-        sorted(tier, key=blocks.__getitem__) for tier in tiers
-    ]
+            last_rank = rank
 
-    modified_tiers = []
+    weights = {}
 
-    last_tier = None
-
-    for tier in reversed(ordered_tiers):
-        if last_tier:
-            modified_tiers.append([tier[0], *last_tier[1:]])
-        else:
-            modified_tiers.append([tier[0]])
-
-        last_tier = tier
-
-    if len(last_tier) > 1:
-        modified_tiers.append(last_tier[1:])
-
-    scores = [0.0] * node_count
-
-    for index, tier in enumerate(modified_tiers):
+    for index, hotkeys in enumerate(rank_hotkeys):
         incentive_pool = WINNER_PERCENTAGE * ((1 - WINNER_PERCENTAGE) ** index)
-        score = incentive_pool / len(tier)
+        score = incentive_pool / len(hotkeys)
 
-        for uid in tier:
-            scores[uid] = score
+        for hotkey in hotkeys:
+            weights[hotkey] = score
 
-    return scores
+    return weights