diff --git a/nodes_sampler.py b/nodes_sampler.py
index a7cfe00..2ac249a 100644
--- a/nodes_sampler.py
+++ b/nodes_sampler.py
@@ -680,50 +680,54 @@ class WanVideoSampler:
         is_looped = False
         context_reference_latent = None
         if context_options is not None:
-            context_schedule = context_options["context_schedule"]
-            context_frames =  (context_options["context_frames"] - 1) // 4 + 1
-            context_stride = context_options["context_stride"] // 4
-            context_overlap = context_options["context_overlap"] // 4
-            context_reference_latent = context_options.get("reference_latent", None)
+            if context_options["context_frames"] <= num_frames:
+                context_schedule = context_options["context_schedule"]
+                context_frames =  (context_options["context_frames"] - 1) // 4 + 1
+                context_stride = context_options["context_stride"] // 4
+                context_overlap = context_options["context_overlap"] // 4
+                context_reference_latent = context_options.get("reference_latent", None)
 
-            # Get total number of prompts
-            num_prompts = len(text_embeds["prompt_embeds"])
-            log.info(f"Number of prompts: {num_prompts}")
-            # Calculate which section this context window belongs to
-            section_size = (latent_video_length / num_prompts) if num_prompts != 0 else 1
-            log.info(f"Section size: {section_size}")
-            is_looped = context_schedule == "uniform_looped"
+                # Get total number of prompts
+                num_prompts = len(text_embeds["prompt_embeds"])
+                log.info(f"Number of prompts: {num_prompts}")
+                # Calculate which section this context window belongs to
+                section_size = (latent_video_length / num_prompts) if num_prompts != 0 else 1
+                log.info(f"Section size: {section_size}")
+                is_looped = context_schedule == "uniform_looped"
 
-            if mocha_embeds is not None:
-                seq_len = (context_frames * 2 + 1 + mocha_num_refs) * (noise.shape[2] * noise.shape[3] // 4)
+                if mocha_embeds is not None:
+                    seq_len = (context_frames * 2 + 1 + mocha_num_refs) * (noise.shape[2] * noise.shape[3] // 4)
+                else:
+                    seq_len = math.ceil((noise.shape[2] * noise.shape[3]) / 4 * context_frames)
+                log.info(f"context window seq len: {seq_len}")
+
+                if context_options["freenoise"]:
+                    log.info("Applying FreeNoise")
+                    # code from AnimateDiff-Evolved by Kosinkadink (https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved)
+                    delta = context_frames - context_overlap
+                    for start_idx in range(0, latent_video_length-context_frames, delta):
+                        place_idx = start_idx + context_frames
+                        if place_idx >= latent_video_length:
+                            break
+                        end_idx = place_idx - 1
+
+                        if end_idx + delta >= latent_video_length:
+                            final_delta = latent_video_length - place_idx
+                            list_idx = torch.tensor(list(range(start_idx,start_idx+final_delta)), device=torch.device("cpu"), dtype=torch.long)
+                            list_idx = list_idx[torch.randperm(final_delta, generator=seed_g)]
+                            noise[:, place_idx:place_idx + final_delta, :, :] = noise[:, list_idx, :, :]
+                            break
+                        list_idx = torch.tensor(list(range(start_idx,start_idx+delta)), device=torch.device("cpu"), dtype=torch.long)
+                        list_idx = list_idx[torch.randperm(delta, generator=seed_g)]
+                        noise[:, place_idx:place_idx + delta, :, :] = noise[:, list_idx, :, :]
+
+                log.info(f"Context schedule enabled: {context_frames} frames, {context_stride} stride, {context_overlap} overlap")
+                from .context_windows.context import get_context_scheduler, create_window_mask, WindowTracker
+                self.window_tracker = WindowTracker(verbose=context_options["verbose"])
+                context = get_context_scheduler(context_schedule)
             else:
-                seq_len = math.ceil((noise.shape[2] * noise.shape[3]) / 4 * context_frames)
-            log.info(f"context window seq len: {seq_len}")
-
-            if context_options["freenoise"]:
-                log.info("Applying FreeNoise")
-                # code from AnimateDiff-Evolved by Kosinkadink (https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved)
-                delta = context_frames - context_overlap
-                for start_idx in range(0, latent_video_length-context_frames, delta):
-                    place_idx = start_idx + context_frames
-                    if place_idx >= latent_video_length:
-                        break
-                    end_idx = place_idx - 1
-
-                    if end_idx + delta >= latent_video_length:
-                        final_delta = latent_video_length - place_idx
-                        list_idx = torch.tensor(list(range(start_idx,start_idx+final_delta)), device=torch.device("cpu"), dtype=torch.long)
-                        list_idx = list_idx[torch.randperm(final_delta, generator=seed_g)]
-                        noise[:, place_idx:place_idx + final_delta, :, :] = noise[:, list_idx, :, :]
-                        break
-                    list_idx = torch.tensor(list(range(start_idx,start_idx+delta)), device=torch.device("cpu"), dtype=torch.long)
-                    list_idx = list_idx[torch.randperm(delta, generator=seed_g)]
-                    noise[:, place_idx:place_idx + delta, :, :] = noise[:, list_idx, :, :]
-
-            log.info(f"Context schedule enabled: {context_frames} frames, {context_stride} stride, {context_overlap} overlap")
-            from .context_windows.context import get_context_scheduler, create_window_mask, WindowTracker
-            self.window_tracker = WindowTracker(verbose=context_options["verbose"])
-            context = get_context_scheduler(context_schedule)
+                log.info("Context frames is larger than total num_frames, disabling context windows")
+                context_options = None
 
         #MTV Crafter
         mtv_input = image_embeds.get("mtv_crafter_motion", None)