diff --git a/benchmarks/user/benchmark.py b/benchmarks/user/benchmark.py
index 21d5c5664b..a2fdbe4731 100644
--- a/benchmarks/user/benchmark.py
+++ b/benchmarks/user/benchmark.py
@@ -66,7 +66,7 @@ def run_op(solver, operator, **options):
         dm = solver.model.dm
         # Because sometime dm is zero, artificially add a non zero slice
         if dm.data.min() == 0 and dm.data.max() == 0:
-            dm.data[..., np.min([25, dm.shape[-1]//4])] = .1
+            dm.data[..., np.min([25, dm.shape_global[-1]//4])] = .1
         return op(dm, **options)
     elif operator == "jacobian_adjoint":
         # I think we want the forward + gradient call, need to merge retvals