diff --git a/tools/compare_vae_temporal_assembly.py b/tools/compare_vae_temporal_assembly.py
index b655cc4..f51fbb8 100644
--- a/tools/compare_vae_temporal_assembly.py
+++ b/tools/compare_vae_temporal_assembly.py
@@ -24,6 +24,17 @@ def diff_stats(label: str, a: torch.Tensor, b: torch.Tensor) -> None:
     print({"label": label, "shape": tuple(a.shape), "max": float(diff.max()), "mean": float(diff.mean())}, flush=True)
 
 
+def tensor_meta(label: str, tensor: torch.Tensor) -> None:
+    print({
+        "label": label,
+        "shape": tuple(tensor.shape),
+        "stride": tuple(tensor.stride()),
+        "dtype": str(tensor.dtype),
+        "contiguous": tensor.is_contiguous(),
+        "storage_offset": tensor.storage_offset(),
+    }, flush=True)
+
+
 def plan(vae, z_len: int):
     pseudo = z_len + vae.token_drop
     pad = (-pseudo) % vae.tokens_chunk_size
@@ -70,6 +81,14 @@ with torch.inference_mode():
             part_u = clip_u[:, :, frame_start:frame_end][:, :, upstream.frame_pre_padding:]
             if split == 0 and prev_d is not None:
                 diff_stats(f"chunk_{chunk_index}_preblend_current", part_d, part_u)
+                if chunk_index == 1:
+                    tensor_meta("prev_d", prev_d)
+                    tensor_meta("prev_u", prev_u)
+                    tensor_meta("part_d", part_d)
+                    tensor_meta("part_u", part_u)
+                    diff_stats("chunk_1_prev", prev_d, prev_u)
+                    diff_stats("chunk_1_direct_blend_contiguous", direct.blend(prev_d.contiguous(), part_d.contiguous(), direct.frame_overlap, -3), upstream.blend(prev_d.contiguous(), part_d.contiguous(), direct.frame_overlap, -3))
+                    diff_stats("chunk_1_cross_respective_contiguous", direct.blend(prev_d.contiguous(), part_d.contiguous(), direct.frame_overlap, -3), upstream.blend(prev_u.contiguous(), part_u.contiguous(), upstream.frame_overlap, -3))
                 diff_stats(f"chunk_{chunk_index}_direct_blend_same_inputs", direct.blend(prev_d, part_d, direct.frame_overlap, -3), upstream.blend(prev_d, part_d, direct.frame_overlap, -3))
                 diff_stats(f"chunk_{chunk_index}_upstream_blend_same_inputs", direct.blend(prev_u, part_u, upstream.frame_overlap, -3), upstream.blend(prev_u, part_u, upstream.frame_overlap, -3))
                 part_d = direct.blend(prev_d, part_d, direct.frame_overlap, -3)