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}, { "label": "upscale_model", "link": null, "name": "model_name", "type": "COMBO", "widget": { "name": "model_name" } }, { "label": "prompt_enhance_model", "link": null, "name": "clip_name_1", "type": "COMBO", "widget": { "name": "clip_name_1" } } ], "mode": 0, "order": 3, "outputs": [ { "links": [ 774 ], "localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO" } ], "pos": [ 2480, 6550 ], "properties": { "cnr_id": "comfy-core", "previewExposures": [], "ver": "0.30.0" }, "size": [ 450, 570 ], "type": "8b4f085c-1bb3-4ecd-aeed-603a8d6d3970", "widgets_values": [ "A close-up of an Arctic hunter's face, his eyes fixed straight ahead, narrowed and locked on something in the far distance directly in front of him, frost dusting his dark beard, one hand slowly reaching toward the rifle slung on his back, his breath quick and shallow, the tension in his jaw visible even through the scarf. 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The wind carries the distant sound of shifting ice, a single low growl rolling across the water.", "unet_name": "ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors", "vae_name": "ltx-2.5-video-vae-bf16.safetensors", "vae_name_1": "ltx-2.5-audio-vae-bf16.safetensors", "value": true, "value_1": 5, "value_2": 1280, "value_3": 720, "value_4": 24 } }, { "bgcolor": "#000", "color": "#222", "flags": {}, "id": 407, "inputs": [], "mode": 0, "order": 0, "outputs": [], "pos": [ 1360, 6550 ], "properties": {}, "size": [ 600, 1280 ], "title": "Note: About LTX-2.5", "type": "MarkdownNote", "widgets_values": [ "# LTX-2.5\n\nLTX-2.5 is Lightricks' open video generation model : fast, local-first, and built for production. Run it locally, fine-tune it for your own use case, or integrate it into your pipeline.\n\n**Key highlights:**\n\n- **Pixel Diffusion** : keyframes-first generation that builds every scene on a grid of high-fidelity keyframes for industry-leading pixel quality\n- **Diffusion Video Decoder** : sharper faces, legible text, fewer smears in fast motion\n- **Native multishot** : one generation yields multiple connected shots holding character, environment, lighting, voice, and style across cuts\n- **Custom Gemma 4 12B text encoder** : retains multiple subjects, actions, lighting, detail, and camera direction across complex prompts\n- **Dedicated Prompt Enhancer** : a lightweight model that expands short prompts into rich cinematic instructions at near-zero extra compute\n- **Auto Duration** : predicts the right clip length from the described action before diffusion begins\n- **Better distilled model** : carries far more quality, prompt adherence, and motion into a smaller, faster variant\n- Carried over from LTX-2.3: native 4K, synchronized audio-video\n\nOfficial model & files: https://huggingface.co/Lightricks/LTX-2.5\n## What this workflow does\n\nThis **Text-to-Video** workflow generates a video directly from a text prompt. Write your prompt, optionally enable the Prompt Enhancer, and the model renders a clip with cinematic pixel quality and synchronized audio.\n\n## Subgraph parameters\n\nThe **Text to Video (LTX-2.5)** node is a subgraph. Click the **Enter subgraph** button at the bottom of the node to open its internal graph, where you can inspect and fine-tune every step of the pipeline (conditioning, sampler, CFG guider, VAE decode, and more).\n\n| Parameter | What it does |\n|---|---|\n| prompt | Text prompt describing the scene, action, lighting, camera, and style |\n| prompt_enhance | Toggle the built-in Prompt Enhancer: expands short prompts into rich cinematic instructions at near-zero extra compute |\n| duration | Clip length in seconds (Auto Duration can predict it from the action) |\n| width / height | Output resolution in pixels (e.g. 1280×720) |\n| seed | Random seed : set a fixed value to reproduce the same result |\n| frame_rate | Frames per second |\n| unet_name | Main model: LTX-2.5 distilled transformer (ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors) |\n| video_vae | Video VAE used for decoding (ltx-2.5-video-vae-bf16.safetensors) |\n| audio_vae | Audio VAE that produces synchronized audio (ltx-2.5-audio-vae-bf16.safetensors) |\n| clip_name | Text encoder: custom Gemma 4 12B with projection (gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors) |\n| upscale_model | Latent upscaler applied before decoding for higher-fidelity output |\n| prompt_enhance_model | Model checkpoint used by the Prompt Enhancer |\n\n## How to use\n\n1. Download the models listed in **Note: Model Links** and place them in ComfyUI's `models/` folder\n2. Write your prompt, optionally toggle **prompt_enhance** for short prompts\n3. Set **duration** / **width** / **height** / **frame_rate** (defaults work well) and hit **Queue**\n4. To dive deeper, click **Enter subgraph** at the bottom of the main node : every internal step (conditioning, sampler, CFG, VAE decode) can be edited there\n" ], "widgets_values_named": { "text": "# LTX-2.5\n\nLTX-2.5 is Lightricks' open video generation model : fast, local-first, and built for production. Run it locally, fine-tune it for your own use case, or integrate it into your pipeline.\n\n**Key highlights:**\n\n- **Pixel Diffusion** : keyframes-first generation that builds every scene on a grid of high-fidelity keyframes for industry-leading pixel quality\n- **Diffusion Video Decoder** : sharper faces, legible text, fewer smears in fast motion\n- **Native multishot** : one generation yields multiple connected shots holding character, environment, lighting, voice, and style across cuts\n- **Custom Gemma 4 12B text encoder** : retains multiple subjects, actions, lighting, detail, and camera direction across complex prompts\n- **Dedicated Prompt Enhancer** : a lightweight model that expands short prompts into rich cinematic instructions at near-zero extra compute\n- **Auto Duration** : predicts the right clip length from the described action before diffusion begins\n- **Better distilled model** : carries far more quality, prompt adherence, and motion into a smaller, faster variant\n- Carried over from LTX-2.3: native 4K, synchronized audio-video\n\nOfficial model & files: https://huggingface.co/Lightricks/LTX-2.5\n## What this workflow does\n\nThis **Text-to-Video** workflow generates a video directly from a text prompt. Write your prompt, optionally enable the Prompt Enhancer, and the model renders a clip with cinematic pixel quality and synchronized audio.\n\n## Subgraph parameters\n\nThe **Text to Video (LTX-2.5)** node is a subgraph. Click the **Enter subgraph** button at the bottom of the node to open its internal graph, where you can inspect and fine-tune every step of the pipeline (conditioning, sampler, CFG guider, VAE decode, and more).\n\n| Parameter | What it does |\n|---|---|\n| prompt | Text prompt describing the scene, action, lighting, camera, and style |\n| prompt_enhance | Toggle the built-in Prompt Enhancer: expands short prompts into rich cinematic instructions at near-zero extra compute |\n| duration | Clip length in seconds (Auto Duration can predict it from the action) |\n| width / height | Output resolution in pixels (e.g. 1280×720) |\n| seed | Random seed : set a fixed value to reproduce the same result |\n| frame_rate | Frames per second |\n| unet_name | Main model: LTX-2.5 distilled transformer (ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors) |\n| video_vae | Video VAE used for decoding (ltx-2.5-video-vae-bf16.safetensors) |\n| audio_vae | Audio VAE that produces synchronized audio (ltx-2.5-audio-vae-bf16.safetensors) |\n| clip_name | Text encoder: custom Gemma 4 12B with projection (gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors) |\n| upscale_model | Latent upscaler applied before decoding for higher-fidelity output |\n| prompt_enhance_model | Model checkpoint used by the Prompt Enhancer |\n\n## How to use\n\n1. Download the models listed in **Note: Model Links** and place them in ComfyUI's `models/` folder\n2. Write your prompt, optionally toggle **prompt_enhance** for short prompts\n3. Set **duration** / **width** / **height** / **frame_rate** (defaults work well) and hit **Queue**\n4. To dive deeper, click **Enter subgraph** at the bottom of the main node : every internal step (conditioning, sampler, CFG, VAE decode) can be edited there\n" } }, { "flags": {}, "id": 409, "inputs": [ { "link": null, "localized_name": "aspect_ratio", "name": "aspect_ratio", "type": "COMBO", "widget": { "name": "aspect_ratio" } }, { "link": null, "localized_name": "megapixels", "name": "megapixels", "type": "FLOAT", "widget": { "name": "megapixels" } }, { "link": null, "localized_name": "multiple", "name": "multiple", "type": "INT", "widget": { "name": "multiple" } } ], "mode": 0, "order": 1, "outputs": [ { "links": [ 792 ], "localized_name": "width", "name": "width", "type": "INT" }, { "links": [ 793 ], "localized_name": "height", "name": "height", "type": "INT" } ], "pos": [ 2140, 6810 ], "properties": { "Node name for S&R": "ResolutionSelector", "cnr_id": "comfy-core", "ver": "0.30.0" }, "showAdvanced": false, "size": [ 270, 170 ], "type": "ResolutionSelector", "widgets_values": [ "16:9 (Widescreen)", 0.9, 32 ], "widgets_values_named": { "aspect_ratio": "16:9 (Widescreen)", "megapixels": 0.9, "multiple": 32 } }, { "bgcolor": "#000", "color": "#222", "flags": {}, "id": 411, "inputs": [], "mode": 0, "order": 2, "outputs": [], "pos": [ 2120, 7060 ], "properties": {}, "size": [ 300, 520 ], "title": "Note: Size Settings Reference", "type": "MarkdownNote", "widgets_values": [ "| megapixels | Aspect | Output (multiple=32) |\n|---|---|---|\n| 0.2 | 16:9 | 608 x 352 |\n| 0.3 | 16:9 | 736 x 416 |\n| 0.4 | 16:9 | 864 x 480 |\n| 0.5 | 16:9 | 960 x 544 |\n| 0.6 | 16:9 | 1056 x 608 |\n| 0.7 | 16:9 | 1152 x 640 |\n| 0.8 | 16:9 | 1216 x 672 |\n| 0.9 | 16:9 | 1280 x 736 |\n| 0.98 | 16:9 | 1344 x 768 |\n| 1.0 | 16:9 | 1376 x 768 |\n| 1.2 | 16:9 | 1504 x 832 |\n| 1.5 | 16:9 | 1664 x 928 |\n| 1.8 | 16:9 | 1824 x 1024 |\n| 2.0 | 16:9 | 1920 x 1088 |\n" ], "widgets_values_named": { "text": "| megapixels | Aspect | Output (multiple=32) |\n|---|---|---|\n| 0.2 | 16:9 | 608 x 352 |\n| 0.3 | 16:9 | 736 x 416 |\n| 0.4 | 16:9 | 864 x 480 |\n| 0.5 | 16:9 | 960 x 544 |\n| 0.6 | 16:9 | 1056 x 608 |\n| 0.7 | 16:9 | 1152 x 640 |\n| 0.8 | 16:9 | 1216 x 672 |\n| 0.9 | 16:9 | 1280 x 736 |\n| 0.98 | 16:9 | 1344 x 768 |\n| 1.0 | 16:9 | 1376 x 768 |\n| 1.2 | 16:9 | 1504 x 832 |\n| 1.5 | 16:9 | 1664 x 928 |\n| 1.8 | 16:9 | 1824 x 1024 |\n| 2.0 | 16:9 | 1920 x 1088 |\n" } } ], "revision": 0, "version": 0.4 }