diff --git a/runs/frontier-fidelity-envelope-v1/analyze_qwen235_fixed_pd_state.py b/runs/frontier-fidelity-envelope-v1/analyze_qwen235_fixed_pd_state.py
index 35ac477..8843574 100644
--- a/runs/frontier-fidelity-envelope-v1/analyze_qwen235_fixed_pd_state.py
+++ b/runs/frontier-fidelity-envelope-v1/analyze_qwen235_fixed_pd_state.py
@@ -183,7 +183,7 @@ def categorized_components(components: dict[str, Any]) -> dict[str, float]:
     }
 
 
-def load_decode_rows(state_root: Path, config: str) -> tuple[list[dict[str, Any]], dict]:
+def load_stage_rows(state_root: Path, config: str) -> tuple[list[dict[str, Any]], dict]:
     result_path = state_root / config / "result.json"
     result = json.loads(result_path.read_text())
     if result.get("status") != "PASS":
@@ -194,8 +194,8 @@ def load_decode_rows(state_root: Path, config: str) -> tuple[list[dict[str, Any]
     rows = []
     for row in load_jsonl(ledger):
         token_counts = [int(value) for value in row["request_num_tokens"]]
-        if not token_counts or any(value != 1 for value in token_counts):
-            continue
+        if not token_counts:
+            raise ValueError(f"empty stage batch in {config}")
         components = categorized_components(
             row["execution_time"]["component_ledger_ms"]
         )
@@ -205,6 +205,9 @@ def load_decode_rows(state_root: Path, config: str) -> tuple[list[dict[str, Any]
         rows.append(
             {
                 "batch_size": len(row["request_ids"]),
+                "decode_requests": sum(value == 1 for value in token_counts),
+                "prefill_requests": sum(value > 1 for value in token_counts),
+                "prefill_tokens": sum(value for value in token_counts if value > 1),
                 "total_time_ms": total,
                 "categories_ms": components,
                 "per_expert_tokens": row.get("per_expert_tokens"),
@@ -215,11 +218,15 @@ def load_decode_rows(state_root: Path, config: str) -> tuple[list[dict[str, Any]
     return rows, result
 
 
-def weighted_component_mean(rows: Iterable[dict[str, Any]]) -> dict[str, float]:
+def weighted_component_mean(
+    rows: Iterable[dict[str, Any]], *, weight_name: str = "batch_size"
+) -> dict[str, float]:
     selected = list(rows)
     if not selected:
         raise ValueError("component mean needs rows")
-    weights = [row["batch_size"] for row in selected]
+    weights = [int(row[weight_name]) for row in selected]
+    if any(weight <= 0 for weight in weights):
+        raise ValueError(f"component weights must be positive: {weight_name}")
     denominator = sum(weights)
     values = {
         category: sum(
@@ -288,13 +295,32 @@ def analyze(real_root: Path, state_root: Path) -> dict[str, Any]:
     sim = {}
     by_batch = {}
     for config in CONFIGS:
-        rows, replay = load_decode_rows(state_root, config)
-        grouped = means_by_batch(rows)
+        rows, replay = load_stage_rows(state_root, config)
+        decode_bearing = [row for row in rows if row["decode_requests"] > 0]
+        pure_decode = [row for row in decode_bearing if row["prefill_requests"] == 0]
+        mixed = [row for row in decode_bearing if row["prefill_requests"] > 0]
+        if not pure_decode:
+            raise ValueError(f"no pure-decode ledger rows for {config}")
+        grouped = means_by_batch(pure_decode)
         by_batch[config] = grouped
         sim[config] = {
-            "decode_only_rows": len(rows),
-            "decode_batch_size": numeric(row["batch_size"] for row in rows),
-            "token_weighted_components_ms": weighted_component_mean(rows),
+            "stage_rows": len(rows),
+            "decode_bearing_rows": len(decode_bearing),
+            "pure_decode_rows": len(pure_decode),
+            "mixed_prefill_decode_rows": len(mixed),
+            "decode_batch_size": numeric(
+                row["decode_requests"] for row in decode_bearing
+            ),
+            "decode_token_weighted_all_step_components_ms": weighted_component_mean(
+                decode_bearing, weight_name="decode_requests"
+            ),
+            "decode_token_weighted_mixed_step_share": sum(
+                row["decode_requests"] for row in mixed
+            )
+            / sum(row["decode_requests"] for row in decode_bearing),
+            "pure_decode_token_weighted_components_ms": weighted_component_mean(
+                pure_decode, weight_name="decode_requests"
+            ),
             "batch_support": {
                 str(batch): value for batch, value in grouped.items()
             },
@@ -307,6 +333,10 @@ def analyze(real_root: Path, state_root: Path) -> dict[str, Any]:
         )
         for config in CONFIGS
     }
+    simulator_internal_contrast = subtract(
+        sim[CONFIGS[1]]["decode_token_weighted_all_step_components_ms"],
+        sim[CONFIGS[0]]["decode_token_weighted_all_step_components_ms"],
+    )
     coverages = [real_reweighted[config]["coverage"] for config in CONFIGS]
     proxy_contrast = None
     if min(coverages) >= 0.8:
@@ -357,6 +387,7 @@ def analyze(real_root: Path, state_root: Path) -> dict[str, Any]:
         },
         "real": real,
         "simulator": sim,
+        "simulator_internal_all_step_tp8_minus_tp4_ms": simulator_internal_contrast,
         "proxy_matched": {
             "method": (
                 "exact batch-size lookup; each simulator config is reweighted to its own "
@@ -390,6 +421,22 @@ def markdown(result: dict[str, Any]) -> str:
             f"| {result['proxy_matched']['configs'][config]['coverage']:.1%} |"
         )
     contrast = result["proxy_matched"]["tp8_minus_tp4_ms"]
+    internal = result["simulator_internal_all_step_tp8_minus_tp4_ms"]
+    lines.extend(
+        [
+            "",
+            "## Frontier internal component contrast over its own executed composition",
+            "",
+            "Decode-token-weighted over both pure-decode and mixed prefill/decode steps.",
+            "",
+            "| Component | TP8 - TP4 (ms/decoded token step) |",
+            "|---|---:|",
+        ]
+    )
+    for name, value in sorted(
+        internal.items(), key=lambda item: abs(item[1]), reverse=True
+    ):
+        lines.append(f"| {name} | {value:+.4f} |")
     if contrast is not None:
         lines.extend(
             [