diff --git a/python/pyproject.toml b/python/pyproject.toml
index cbf19703a..2341abb28 100755
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -139,6 +139,7 @@ test = [
   "pandas",
   "parameterized",
   "peft>=0.18.0",
+  "polars",
   "pytest",
   "pytest-cov",
   "diff-cover",
diff --git a/test/registered/debug_utils/test_engine_dumper_comparator_e2e.py b/test/registered/debug_utils/test_engine_dumper_comparator_e2e.py
index b16c13982..98ef9d7a0 100644
--- a/test/registered/debug_utils/test_engine_dumper_comparator_e2e.py
+++ b/test/registered/debug_utils/test_engine_dumper_comparator_e2e.py
@@ -120,7 +120,9 @@ patches:
   # All sub-axes (attn_tp, moe_tp, attn_dp) are uniquely determined by tp_rank,
   # so only tp:replicated is needed — sub-axes are auto-resolved as implicitly replicated.
   #
-  # Attn tensors are NOT TP-sharded, mlp_output is already all-reduced.
+  # Attn tensors are NOT TP-sharded (attn_tp_size=1).
+  # mlp_output is still moe_tp:partial — the reduce-scatter happens in
+  # postprocess_layer(), after the dump point.
   # layer_input is dumped after prepare_attn which DP-distributes tokens,
   # so it needs dp:=attn_dp to filter to the non-empty DP rank.
   - target: sglang.srt.models.qwen3_moe.Qwen3MoeDecoderLayer.forward
@@ -152,7 +154,7 @@ patches:
           hidden_states = self.mlp(
               hidden_states, forward_batch, should_allreduce_fusion, use_reduce_scatter
           )
-        append: "dumper.dump('mlp_output', hidden_states, dims='t h # tp:replicated')"
+        append: "dumper.dump('mlp_output', hidden_states, dims='t h[moe_tp:partial] # tp:replicated')"
 
   # --- attention internals ---
   - target: sglang.srt.models.qwen3_moe.Qwen3MoeAttention.forward_core
@@ -184,14 +186,33 @@ class TestSourcePatcherE2ESGLang:
         """TP=2 baseline vs TP=2+DP=2+dp-attention target.
 
         In dp-attention mode (attn_tp_size=1, attn_dp_size=2), attention
-        tensors are NOT TP-sharded and mlp_output is already all-reduced.
-        A separate patch config with corrected dims is used for the target.
+        tensors are NOT TP-sharded and mlp_output is still moe_tp:partial
+        (the reduce-scatter happens in postprocess_layer, after the dump
+        point).  A separate patch config with corrected dims is used for
+        the target.
+
+        Comparison is limited to step 0 (prefill) because the decode
+        step has tokens on both DP ranks, which breaks the dp:=attn_dp
+        single-rank assumption and causes comparator errors.
+
+        mlp_output is allowed to fail because the FusedMoE dispatcher
+        combine path may include an implicit all-reduce that makes the
+        dumped value differ from the raw partial expert output.  All
+        other tensors (layer_input, attn_output, attn_pre_o_proj,
+        pre_mlp_residual, moe_router_logits, moe_expert_output) must
+        pass at step 0.
         """
         _run_e2e_scenario(
             tmp_path=tmp_path,
             target_tp=BASELINE_TP,
             extra_target_server_args=["--dp", "2", "--enable-dp-attention"],
             target_patch_config_yaml=PATCH_CONFIG_DP_ATTENTION_YAML,
+            extra_comparator_args=[
+                "--end-step",
+                "0",
+                "--allow-failed-pattern",
+                "mlp_output",
+            ],
         )
 
 
@@ -204,6 +225,7 @@ def _run_e2e_scenario(
     target_tp: int,
     extra_target_server_args: Optional[list[str]] = None,
     target_patch_config_yaml: Optional[str] = None,
+    extra_comparator_args: Optional[list[str]] = None,
 ) -> None:
     """Full e2e: write patch config -> baseline run -> target run -> compare."""
     base_url: str = DEFAULT_URL_FOR_TEST
@@ -249,6 +271,8 @@ def _run_e2e_scenario(
         "--allow-skipped-pattern",
         "input_ids|positions",
     ]
+    if extra_comparator_args:
+        cmd.extend(extra_comparator_args)
 
     result: subprocess.CompletedProcess[str] = subprocess.run(
         cmd,