{ "id": "0112e9af-5129-48ba-af78-92c40ac40b40", "revision": 0, "last_node_id": 265, "last_link_id": 392, "nodes": [ { "id": 254, "type": "MarkdownNote", "pos": [ 790, 2310 ], "size": [ 440, 1640 ], "flags": {}, "order": 0, "mode": 0, "inputs": [], "outputs": [], "title": "Note: About LTX-2.5", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "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 **First & Last Frame** workflow interpolates between two images. Load a first and a last frame, and the model generates the connected shots in between : holding character, environment, lighting, and style across the transition, with synchronized audio.\n\n## Subgraph parameters\n\nThe **First & Last Frame 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| first_frame | Starting image of the transition (load your own image in **Load First Frame**) |\n| last_frame | Ending image of the transition (load your own image in **Load Last Frame**) |\n| prompt | Text prompt describing the motion, scene, 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. 1280Γ—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| 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. Replace the images in **Load First Frame** and **Load Last Frame** with your own start/end frames\n3. Write a prompt describing the transition, optionally toggle **prompt_enhance** for short prompts\n4. Set **duration** / **width** / **height** / **frame_rate** (defaults work well) and hit **Queue**\n5. 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" ], "color": "#222", "bgcolor": "#000" }, { "id": 255, "type": "MarkdownNote", "pos": [ 190, 2320 ], "size": [ 550, 880 ], "flags": {}, "order": 1, "mode": 0, "inputs": [], "outputs": [], "title": "Note: Model Links", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "Guide: [Subgraph](https://docs.comfy.org/interface/features/subgraph)\n\n## Model Links\n\n**Input Assets** \n\n- [robot_hand_back.png](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/robot_hand_back.png) β€” required workflow input (`input/robot_hand_back.png`)\n- [robot_hand_energy.png](https://raw.githubusercontent.com/Comfy-Org/workflow_templates/refs/heads/main/input/robot_hand_energy.png) β€” required workflow input (`input/robot_hand_energy.png`)\n\n**diffusion_models**\n\n- [ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors](https://huggingface.co/Lightricks/LTX-2.5/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors)\n\n**vae**\n\n- [ltx-2.5-video-vae-bf16.safetensors](https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-video-vae-bf16.safetensors)\n- [ltx-2.5-audio-vae-bf16.safetensors](https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-audio-vae-bf16.safetensors)\n\n**text_encoders**\n\n- [gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors](https://huggingface.co/Lightricks/LTX-2.5/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors)\n- [gemma4_e2b_it_bf16.safetensors](https://huggingface.co/Comfy-Org/gemma-4/resolve/main/text_encoders/gemma4_e2b_it_bf16.safetensors)\n\n\n## Model Storage Location\n\n```\nπŸ“‚ ComfyUI/\nβ”œβ”€β”€ πŸ“‚ models/\nβ”‚ β”œβ”€β”€ πŸ“‚ diffusion_models/\nβ”‚ β”‚ └── ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors\nβ”‚ β”œβ”€β”€ πŸ“‚ vae/\nβ”‚ β”‚ β”œβ”€β”€ ltx-2.5-video-vae-bf16.safetensors\nβ”‚ β”‚ └── ltx-2.5-audio-vae-bf16.safetensors\nβ”‚ └── πŸ“‚ text_encoders/\nβ”‚ β”œβ”€β”€ gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors\nβ”‚ └── gemma4_e2b_it_bf16.safetensors\n```\n\n## Report Issue\n\nNote: Please update ComfyUI first ([guide](https://docs.comfy.org/installation/update_comfyui)) and prepare required models. Desktop/Cloud updates follow stable releases, so some nightly-supported models may not be available yet.\n\n- Cannot run / runtime errors: [ComfyUI/issues](https://github.com/comfyanonymous/ComfyUI/issues)\n- UI / frontend issues: [ComfyUI_frontend/issues](https://github.com/Comfy-Org/ComfyUI_frontend/issues)\n- Workflow issues: [workflow_templates/issues](https://github.com/Comfy-Org/workflow_templates/issues)\n" ], "color": "#222", "bgcolor": "#000" }, { "id": 258, "type": "MarkdownNote", "pos": [ 190, 2170 ], "size": [ 340, 90 ], "flags": {}, "order": 2, "mode": 0, "inputs": [], "outputs": [], "title": "Note: Model Links", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "Before you download all the models, please make sure you have granted access to [LTX-2.5](https://huggingface.co/Lightricks/LTX-2.5) first." ], "color": "#432", "bgcolor": "#653" }, { "id": 31, "type": "LoadImage", "pos": [ 1430.0795061295175, 2285.769503760189 ], "size": [ 430, 580 ], "flags": {}, "order": 3, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 367 ] }, { "name": "MASK", "type": "MASK", "links": null } ], "title": "Load First Frame", "properties": { "cnr_id": "comfy-core", "ver": "0.8.2", "Node name for S&R": "LoadImage", "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.2" } }, "widgets_values": [ "i_00084_.png", "image" ] }, { "id": 259, "type": "ResolutionSelector", "pos": [ 1917.6603618743081, 2678.516518909564 ], "size": [ 270, 170 ], "flags": {}, "order": 4, "mode": 0, "showAdvanced": false, "inputs": [], "outputs": [ { "name": "width", "type": "INT", "links": [ 387 ] }, { "name": "height", "type": "INT", "links": [ 388 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "ResolutionSelector", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "16:9 (Widescreen)", 1.5, 32 ] }, { "id": 260, "type": "MarkdownNote", "pos": [ 1913.2016877297306, 2959.4234963068625 ], "size": [ 300, 520 ], "flags": {}, "order": 5, "mode": 0, "inputs": [], "outputs": [], "title": "Note: Size Settings Reference", "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "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" ], "color": "#222", "bgcolor": "#000" }, { "id": 39, "type": "LoadImage", "pos": [ 1433.905373956857, 2923.218925208631 ], "size": [ 440, 570 ], "flags": {}, "order": 6, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 368 ] }, { "name": "MASK", "type": "MASK", "links": null } ], "title": "Load Last Frame", "properties": { "cnr_id": "comfy-core", "ver": "0.8.2", "Node name for S&R": "LoadImage", "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.2" } }, "widgets_values": [ "krea2/i_00085_.png [output]", "image" ] }, { "id": 68, "type": "SaveVideo", "pos": [ 3003.422972548701, 2281.5886950541535 ], "size": [ 1110, 106 ], "flags": {}, "order": 8, "mode": 4, "inputs": [ { "name": "video", "type": "VIDEO", "link": 369 } ], "outputs": [ { "name": "video", "type": "VIDEO", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.14.1", "Node name for S&R": "SaveVideo", "enableTabs": false, "tabWidth": 65, "tabXOffset": 10, "hasSecondTab": false, "secondTabText": "Send Back", "secondTabOffset": 80, "secondTabWidth": 65, "ue_properties": { "widget_ue_connectable": {}, "version": "7.7", "input_ue_unconnectable": {} } }, "widgets_values": [ "video/ltx2.5_flf2v", "auto", "auto" ] }, { "id": 251, "type": "cf70afc4-5a03-47ce-8210-734b1de6c6bc", "pos": [ 2302.1607953465423, 2298.158869505415 ], "size": [ 520, 710 ], "flags": {}, "order": 7, "mode": 0, "inputs": [ { "label": "first_frame", "name": "input", "type": "IMAGE,MASK", "link": 367 }, { "label": "last_frame", "name": "input_1", "type": "IMAGE,MASK", "link": 368 }, { "label": "prompt", "name": "value", "type": "STRING", "widget": { "name": "value" }, "link": null }, { "label": "prompt_enhance", "name": "value_1", "type": "BOOLEAN", "widget": { "name": "value_1" }, "link": null }, { "label": "duration", "name": "value_2", "type": "INT", "widget": { "name": "value_2" }, "link": null }, { "label": "width", "name": "value_3", "type": "INT", "widget": { "name": "value_3" }, "link": 387 }, { "label": "height", "name": "value_4", "type": "INT", "widget": { "name": "value_4" }, "link": 388 }, { "label": "fram_rate", "name": "value_5", "type": "INT", "widget": { "name": "value_5" }, "link": null }, { "label": "video_vae", "name": "vae_name", "type": "COMBO", "widget": { "name": "vae_name" }, "link": null }, { "label": "audio_vae", "name": "vae_name_1", "type": "COMBO", "widget": { "name": "vae_name_1" }, "link": null }, { "label": "prompt_enhance_model", "name": "clip_name_1", "type": "COMBO", "widget": { "name": "clip_name_1" }, "link": null } ], "outputs": [ { "name": "VIDEO", "type": "VIDEO", "links": [ 369 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "previewExposures": [], "ue_properties": { "widget_ue_connectable": { "value": true, "value_1": true, "value_2": true, "value_3": true, "value_4": true, "value_5": true, "vae_name": true, "vae_name_1": true, "clip_name_1": true }, "version": "7.8", "input_ue_unconnectable": {} } }, "widgets_values": [ "The video begins exactly from the first frame: a photorealistic golden retriever stands at the beginning of a wide empty beach during golden hour, facing the woman waiting far ahead near the shoreline. The dog looks directly toward her with an excited, focused expression, its ears relaxed, tail slightly raised, and body naturally balanced on all four paws. Gentle ocean waves move along the shoreline to one side while warm sunlight creates a bright golden rim around the dog's fur, and the wet sand reflects the orange sky. For the first moment, the dog remains still, clearly recognizing the woman in the distance, while a gentle ocean breeze moves its fur and the woman's clothing.\n\nThe dog suddenly becomes excited and lowers its body slightly, shifting its weight backward onto its rear legs before naturally pushing forward into a run. Its front legs extend forward and its rear legs push against the damp sand, beginning a realistic four-legged gallop toward the woman. The camera immediately begins a smooth low tracking movement backward in front of the dog, staying close to ground level and maintaining a clear view of its face, chest, front legs, and moving body. The dog's ears bounce naturally with each stride, its tail moves rhythmically behind it, and its red collar shifts subtly against its neck.\n\nAs the dog gains speed, its paws repeatedly make realistic contact with the wet sand in a natural four-legged running rhythm. Each landing creates tiny impressions in the damp surface, leaving a visible trail of pawprints behind the dog, while occasional grains of sand are lightly displaced by its paws. The dog's fur responds naturally to the running motion and wind, with individual strands around its ears, neck, and chest moving subtly. The woman's figure remains clearly visible ahead, gradually becoming larger as the dog closes the distance.\n\nThe camera continues tracking backward at approximately the same speed as the running dog, maintaining a low three-quarter front perspective. The dog's face remains the primary subject while the beach and ocean move naturally behind it, creating subtle cinematic background motion. The dog briefly glances toward the waves without changing its running direction, then immediately turns its attention back toward the woman. Its expression remains happy and eager, with its mouth slightly open and ears moving naturally as it runs.\n\nThe warm sunset becomes more prominent as the camera continues moving backward. Golden light catches the dog's moving fur, creating a soft glowing edge around its ears, back, and tail. Small reflections of the sunset appear across the wet sand, while gentle waves roll parallel to the dog's path. A thin layer of sea mist remains near the horizon, distant rocks stay fixed in the background, and a few seabirds glide far above the ocean without coming close to the subjects.\n\nAs the dog approaches the woman, the camera gradually increases its distance slightly and transitions from the low close tracking shot into a wider medium tracking composition, allowing both the dog and woman to remain visible in the same frame. The woman notices the approaching dog and naturally bends slightly forward, smiling and opening her arms toward it. She remains stationary while waiting for the dog, allowing the dog to remain the primary moving subject.\n\nThe dog continues running directly toward her, gradually reducing its speed as it gets within a few meters. Its stride becomes shorter and slower, its body rises from the running posture into a natural standing posture, and its paws make increasingly gentle contact with the wet sand. The camera smoothly moves from directly in front of the dog toward a low three-quarter side angle, revealing the woman clearly behind it and maintaining visual continuity with the final frame.\n\nThe dog slows to a gentle stop directly in front of the woman without jumping or making any complicated movement. Its front paws settle naturally into the damp sand while its tail continues wagging happily and its ears relax. A few tiny grains of sand move around its paws as it comes to rest, and the woman bends down toward the dog with both hands reaching forward to greet it. The dog looks upward toward her face with an excited, affectionate expression.\n\nThe camera makes one final subtle adjustment into the exact composition of the last frame: the woman is crouched beside the shoreline with her hands reaching toward the golden retriever, while the dog stands directly in front of her after completing the run. The ocean rolls gently behind them, the wet sand reflects the orange and pink sunset, and the dog's golden fur and the woman's silhouette are illuminated by warm rim light. Hold this final composition for the remaining moment as the woman gently touches the dog's head, the dog remains calm and happy, and a small wave rolls softly across the background.\n\nPhotorealistic live-action cinematography, exact golden retriever identity maintained from the first frame through the final frame, exact red collar maintained throughout, consistent fur color and markings, anatomically correct canine proportions, realistic four-legged running gait, physically believable weight transfer, natural leg coordination, realistic paw contact with wet sand, subtle sand displacement, believable ear movement, realistic tail movement, detailed individual fur strands, natural mouth and facial movement, realistic human anatomy and motion, physically accurate ocean waves, wet sand reflections, atmospheric sea mist, warm golden-hour sunlight, realistic sunset exposure, cinematic 35mm lens, low-angle tracking camera, smooth camera movement synchronized with the dog's running speed, natural motion blur during the faster running section, gradual camera distance change, realistic depth of field, subtle focus transitions, detailed environmental textures, natural wind interaction, subtle film grain, polished cinematic live-action quality.\n\nNo cuts, no scene changes, no teleportation, no sudden camera jumps, no changes to the dog's breed, fur color, facial features, collar, or body proportions, no additional dogs, no extra people, no unnatural limb movement, no floating paws, no distorted legs, no exaggerated jumping, no sudden acceleration, and no complex interaction with the environment.", false, 20, 1280, 720, 607334310286239, 24, "ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors", "ltx-2.5-video-vae-bf16.safetensors", "ltx-2.5-audio-vae-bf16.safetensors", "gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors", "gemma4_e2b_it_bf16.safetensors" ] } ], "links": [ [ 367, 31, 0, 251, 0, "IMAGE" ], [ 368, 39, 0, 251, 1, "IMAGE" ], [ 369, 251, 0, 68, 0, "VIDEO" ], [ 387, 259, 0, 251, 5, "INT" ], [ 388, 259, 1, 251, 6, "INT" ] ], "groups": [], "definitions": { "subgraphs": [ { "id": "cf70afc4-5a03-47ce-8210-734b1de6c6bc", "version": 1, "state": { "lastGroupId": 9, "lastNodeId": 265, "lastLinkId": 392, "lastRerouteId": 0 }, "revision": 0, "config": {}, "name": "First & Last Frame to Video (LTX-2.5)", "inputNode": { "id": -10, "bounding": [ -280, 2210, 183.814453125, 328 ] }, "outputNode": { "id": -20, "bounding": [ 3540, 2261, 128, 68 ] }, "inputs": [ { "id": "9ef90062-29a7-4a94-95c7-1fced49f3705", "name": "input", "type": "IMAGE,MASK", "linkIds": [ 325 ], "localized_name": "input", "label": "first_frame", "pos": [ -120.185546875, 2234 ] }, { "id": "394b4186-1545-4d8e-a81e-2fdd06c7d86a", "name": "input_1", "type": "IMAGE,MASK", "linkIds": [ 326 ], "localized_name": "input_1", "label": "last_frame", "pos": [ -120.185546875, 2254 ] }, { "id": "06e99847-4ff4-4b47-89af-703de88f32c6", "name": "value", "type": "STRING", "linkIds": [ 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