diff --git a/CUDA_GRAPH_SYNC_INVENTORY.md b/CUDA_GRAPH_SYNC_INVENTORY.md
index ee3025ec..1602202f 100644
--- a/CUDA_GRAPH_SYNC_INVENTORY.md
+++ b/CUDA_GRAPH_SYNC_INVENTORY.md
@@ -4,7 +4,17 @@
 **Source:** Section A detector run + manual code grep (Section B checklist)
 **Target:** single_shot_inference.py decode forward (1 token step, T=1)
 
-## Summary
+## B200 Detector Results (first run)
+
+Method 1 (sync debug mode): **1 violation** caught
+- `dec_tid_buf[0] = all_tokens[-1]` — CPU→GPU sync from writing Python int to GPU tensor
+- **FIXED**: Use pinned CPU buffer + copy_
+
+Method 2 (graph capture L0): **FAIL**
+- `expert_offsets[g] = (g + 1) * padded_rows_per_group` — CPU→GPU sync in Python loop
+- **FIXED**: Pre-allocated range tensor + element-wise multiply
+
+Both fixes committed and pushed. Re-running detector to verify.
 
 The decode forward has **numerous device→host sync violations** that must be fixed before CUDA graph capture can succeed. The violations fall into clear categories below.
 
diff --git a/dsv4/layers/linear.py b/dsv4/layers/linear.py
index 007f6169..32b53473 100644
--- a/dsv4/layers/linear.py
+++ b/dsv4/layers/linear.py
@@ -156,7 +156,10 @@ class Nvfp4Linear:
             f"scale_a_buf too small: {buf.shape} < ({padded_rows}, {padded_cols})"
         buf.view(torch.uint8).zero_()
         buf[:num_rows, :num_cols] = x_sf
-        swizzled_flat = pad_and_swizzle_single(buf)
+        # Pass correctly-sized VIEW to swizzle — the swizzle operates on
+        # (padded_rows, padded_cols) not the full max-size buffer.
+        view = buf[:padded_rows, :padded_cols]
+        swizzled_flat = pad_and_swizzle_single(view)
         return swizzled_flat.reshape(padded_rows, padded_cols)
 
     def compute_activation_global_scale(self, hidden_states_sample):
diff --git a/dsv4/layers/shared_expert.py b/dsv4/layers/shared_expert.py
index 5b7b63f9..cb936673 100644
--- a/dsv4/layers/shared_expert.py
+++ b/dsv4/layers/shared_expert.py
@@ -216,7 +216,9 @@ class Nvfp4SharedExpert:
             f"padded_x_sf_buf too small: {buf.shape} < ({padded_rows}, {padded_cols})"
         buf.view(torch.uint8).zero_()
         buf[:num_rows, :num_cols] = x_sf
-        swizzled_flat = pad_and_swizzle_single(buf)
+        # Pass correctly-sized VIEW to swizzle — avoids processing the full max-size buffer
+        view = buf[:padded_rows, :padded_cols]
+        swizzled_flat = pad_and_swizzle_single(view)
         return swizzled_flat.reshape(padded_rows, padded_cols)
 
     def compute_activation_global_scales(self, hidden_states_sample):