diff --git a/headswap_ltx_masked_sampler.py b/headswap_ltx_masked_sampler.py
index f0ec6de..91a6edb 100644
--- a/headswap_ltx_masked_sampler.py
+++ b/headswap_ltx_masked_sampler.py
@@ -325,6 +325,22 @@ def _mask_to_latent(masks, vae, latent_t, latent_h, latent_w):
 # node
 # ─────────────────────────────────────────────────────────────────────────────
 
+def _keep_new_frames(samples, produced, total):
+    """Drop the head a chunk shares with the one before it.
+
+    Chunks are sampled with an overlap for continuity, so consecutive chunks
+    cover some of the same frames. Concatenating them whole makes the clip
+    longer than it is and every frame after the first seam lands on the wrong
+    moment -- and, with per-frame crop boxes, in the wrong box. Keeping only
+    what each chunk adds makes the concatenation exactly `total` frames.
+    """
+    have = samples.shape[2]
+    new = max(0, min(have, total - produced))
+    if new < have:
+        samples = samples[:, :, have - new:]
+    return samples, produced + samples.shape[2]
+
+
 def _inject_transformer_options(guider, model_patcher, debug=False):
     """Copy the patched model's transformer_options INTO the guider's own dict.
 
@@ -715,6 +731,7 @@ class BFSHeadSwapMaskedSampler:
         mc = LTXMultipleControls()
         out_latents = []
         injections = []
+        produced = 0
         try:
             for idx, (a, b) in enumerate(chunks):
                 g = guide[a:b]
@@ -792,6 +809,7 @@ class BFSHeadSwapMaskedSampler:
                 chunk = _Loop._sample_chunk(m, noise, sampler, sigmas, gd, latent, seed_offset=idx)
                 got = chunk["samples"]
                 if len(chunks) > 1 and not getattr(got, "is_nested", False):
+                    got, produced = _keep_new_frames(got, produced, lat_t_total)
                     # a long clip is many chunks: holding them all on the sampling
                     # device grows VRAM with the clip while the model is still loaded
                     got = got.to(comfy.model_management.intermediate_device())
diff --git a/pyproject.toml b/pyproject.toml
index b622c08..2d41f4b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "bfsnodes"
 description = "Custom ComfyUI nodes for reference-guided video: the BFS Sampler (guide-driven IC-LoRAs with auto-configured crop, mask inpainting and temporal chunking in one node), LTX Multiple Controls and Identity Transfer (IPT2V reference + source-phase RoPE), LTXV Edit Anything, Head-Swap/Anime2Real Bernini conditioning, the AMV Guide Builder, and MiniMax-H3 single-frame VAE loaders with tile control."
-version = "1.39.1"
+version = "1.39.2"
 license = {file = "LICENSE"}
 dependencies = [
     "torch",
diff --git a/tests/test_headswap_auto_config.py b/tests/test_headswap_auto_config.py
index 2d4a2d0..d9be262 100644
--- a/tests/test_headswap_auto_config.py
+++ b/tests/test_headswap_auto_config.py
@@ -249,6 +249,42 @@ class PasteBackWithoutCropTest(unittest.TestCase):
         self.assertEqual(out.shape, self.original.shape)
 
 
+class ChunkOverlapTest(unittest.TestCase):
+    """Chunks are sampled with an overlap for continuity. Concatenating them
+    whole made the clip longer than it is, so every frame after the first seam
+    landed on the wrong moment -- and, with per-frame crop boxes, in the wrong
+    box. 97 frames at tile 72 / overlap 16 produced 15 latent frames where the
+    clip has 13."""
+
+    @staticmethod
+    def run_chunks(lat_per_chunk, total):
+        produced, out = 0, []
+        for t in lat_per_chunk:
+            got, produced = NODE._keep_new_frames(torch.zeros(1, 4, t, 2, 2), produced, total)
+            out.append(got)
+        return torch.cat(out, dim=2)
+
+    def test_the_concatenation_is_exactly_the_clip(self):
+        self.assertEqual(self.run_chunks([9, 6], 13).shape[2], 13)
+
+    def test_it_keeps_each_chunk_s_tail_not_its_head(self):
+        a = torch.zeros(1, 4, 9, 2, 2)
+        b = torch.arange(6, dtype=torch.float32).view(1, 1, 6, 1, 1).expand(1, 4, 6, 2, 2).clone()
+        _, produced = NODE._keep_new_frames(a, 0, 13)
+        kept, _ = NODE._keep_new_frames(b, produced, 13)
+        self.assertEqual(kept.shape[2], 4)
+        self.assertEqual(kept[0, 0, 0, 0, 0].item(), 2.0)   # frames 2..5, the new tail
+
+    def test_a_single_chunk_is_untouched(self):
+        got, produced = NODE._keep_new_frames(torch.zeros(1, 4, 13, 2, 2), 0, 13)
+        self.assertEqual(got.shape[2], 13)
+        self.assertEqual(produced, 13)
+
+    def test_it_never_returns_more_than_is_left(self):
+        got, _ = NODE._keep_new_frames(torch.zeros(1, 4, 9, 2, 2), 12, 13)
+        self.assertEqual(got.shape[2], 1)
+
+
 class NoShadowedModulesTest(unittest.TestCase):
     """`import comfy.x` inside a function binds `comfy` as a LOCAL for the whole
     function, so every earlier comfy.* use in it raises UnboundLocalError. It