diff --git a/comfy_extras/nodes_void.py b/comfy_extras/nodes_void.py
index 4e9f77930..dd03eda6a 100644
--- a/comfy_extras/nodes_void.py
+++ b/comfy_extras/nodes_void.py
@@ -1,3 +1,5 @@
+import logging
+
 import nodes
 import node_helpers
 import torch
@@ -9,6 +11,29 @@ from comfy.utils import model_trange as trange
 from comfy_api.latest import io, ComfyExtension
 from typing_extensions import override
 
+TEMPORAL_COMPRESSION = 4
+PATCH_SIZE_T = 2
+
+
+def _valid_void_length(length: int) -> int:
+    """Round ``length`` down to a value that produces an even latent_t.
+
+    VOID / CogVideoX-Fun-V1.5 uses patch_size_t=2, so the VAE-encoded latent
+    must have an even temporal dimension. If latent_t is odd, the transformer
+    pad_to_patch_size circular-wraps an extra latent frame onto the end; after
+    the post-transformer crop the last real latent frame has been influenced
+    by the wrapped phantom frame, producing visible jitter and "disappearing"
+    subjects near the end of the decoded video. Rounding down fixes this.
+    """
+    latent_t = ((length - 1) // TEMPORAL_COMPRESSION) + 1
+    if latent_t % PATCH_SIZE_T == 0:
+        return length
+    # Round latent_t down to the nearest multiple of PATCH_SIZE_T, then invert
+    # the ((length - 1) // TEMPORAL_COMPRESSION) + 1 formula. Floor at 1 frame
+    # so we never return a non-positive length.
+    target_latent_t = max(PATCH_SIZE_T, (latent_t // PATCH_SIZE_T) * PATCH_SIZE_T)
+    return (target_latent_t - 1) * TEMPORAL_COMPRESSION + 1
+
 
 class VOIDQuadmaskPreprocess(io.ComfyNode):
     """Preprocess a quadmask video for VOID inpainting.
@@ -88,8 +113,10 @@ class VOIDInpaintConditioning(io.ComfyNode):
                 io.Mask.Input("quadmask", tooltip="Preprocessed quadmask from VOIDQuadmaskPreprocess [T, H, W]"),
                 io.Int.Input("width", default=672, min=16, max=nodes.MAX_RESOLUTION, step=8),
                 io.Int.Input("height", default=384, min=16, max=nodes.MAX_RESOLUTION, step=8),
-                io.Int.Input("length", default=49, min=1, max=nodes.MAX_RESOLUTION, step=1,
-                             tooltip="Number of pixel frames to process"),
+                io.Int.Input("length", default=45, min=1, max=nodes.MAX_RESOLUTION, step=1,
+                             tooltip="Number of pixel frames to process. For CogVideoX-Fun-V1.5 "
+                                     "(patch_size_t=2), latent_t must be even — lengths that "
+                                     "produce odd latent_t are rounded down (e.g. 49 → 45)."),
                 io.Int.Input("batch_size", default=1, min=1, max=64),
             ],
             outputs=[
@@ -103,8 +130,17 @@ class VOIDInpaintConditioning(io.ComfyNode):
     def execute(cls, positive, negative, vae, video, quadmask,
                 width, height, length, batch_size) -> io.NodeOutput:
 
-        temporal_compression = 4
-        latent_t = ((length - 1) // temporal_compression) + 1
+        adjusted_length = _valid_void_length(length)
+        if adjusted_length != length:
+            logging.warning(
+                "VOIDInpaintConditioning: rounding length %d down to %d so that "
+                "latent_t is even (required by CogVideoX-Fun-V1.5 patch_size_t=2). "
+                "Using odd latent_t causes the last frame to be corrupted by "
+                "circular padding.", length, adjusted_length,
+            )
+            length = adjusted_length
+
+        latent_t = ((length - 1) // TEMPORAL_COMPRESSION) + 1
         latent_h = height // 8
         latent_w = width // 8
 
@@ -188,8 +224,9 @@ class VOIDWarpedNoise(io.ComfyNode):
                 io.Image.Input("video", tooltip="Pass 1 output video frames [T, H, W, 3]"),
                 io.Int.Input("width", default=672, min=16, max=nodes.MAX_RESOLUTION, step=8),
                 io.Int.Input("height", default=384, min=16, max=nodes.MAX_RESOLUTION, step=8),
-                io.Int.Input("length", default=49, min=1, max=nodes.MAX_RESOLUTION, step=1,
-                             tooltip="Number of pixel frames"),
+                io.Int.Input("length", default=45, min=1, max=nodes.MAX_RESOLUTION, step=1,
+                             tooltip="Number of pixel frames. Rounded down to make latent_t "
+                                     "even (patch_size_t=2 requirement), e.g. 49 → 45."),
                 io.Int.Input("batch_size", default=1, min=1, max=64),
             ],
             outputs=[
@@ -211,8 +248,16 @@ class VOIDWarpedNoise(io.ComfyNode):
                 "VOIDWarpedNoise requires the 'rp' package. Install with: pip install rp"
             )
 
-        temporal_compression = 4
-        latent_t = ((length - 1) // temporal_compression) + 1
+        adjusted_length = _valid_void_length(length)
+        if adjusted_length != length:
+            logging.warning(
+                "VOIDWarpedNoise: rounding length %d down to %d so that "
+                "latent_t is even (required by CogVideoX-Fun-V1.5 patch_size_t=2).",
+                length, adjusted_length,
+            )
+            length = adjusted_length
+
+        latent_t = ((length - 1) // TEMPORAL_COMPRESSION) + 1
         latent_h = height // 8
         latent_w = width // 8