بنقرة واحدة
ltxv2-video
// Build LTX-V2 19B video workflows — text-to-video, image-to-video, distilled model, camera control LoRAs, and two-stage upscaling
// Build LTX-V2 19B video workflows — text-to-video, image-to-video, distilled model, camera control LoRAs, and two-stage upscaling
Authoring & publishing ComfyUI custom nodes to the Comfy Registry — node structure, pyproject.toml spec, comfy-cli publishing, and CI
Authoring ComfyUI v2 frontend extensions with @comfyorg/extension-api — defineNode/defineExtension/defineWidget, shell UI (sidebar tabs, commands, hotkeys), typed events, and handles. Use when writing or editing ComfyUI web-UI extension code (custom node JS, sidebar panels, widgets).
Build Qwen Image Edit workflows — model loading, conditioning, LoRAs, prompt patterns, and XY plot testing
Build WAN 2.2 First-Last-Frame video workflows — native dual hi-lo (required), and WanVideoWrapper VACE approaches
Core ComfyUI knowledge — workflow format, node types, pipeline patterns, and MCP tool usage
Full production pipeline — story to scenes, Z-Image start frames, Qwen Edit end frames, WAN FLF video clips, ffmpeg concatenation
| name | ltxv2-video |
| description | Build LTX-V2 19B video workflows — text-to-video, image-to-video, distilled model, camera control LoRAs, and two-stage upscaling |
| globs | ["**/*.json"] |
LTX-V2 (LTX-2) is a 19-billion parameter DiT-based video foundation model from Lightricks. It uses a Gemma 3 12B text encoder and supports both text-to-video (T2V) and image-to-video (I2V). Key features:
| Component | Node | Model | Notes |
|---|---|---|---|
| Checkpoint | CheckpointLoaderSimple | ltx-2-19b-distilled.safetensors | 41GB bf16, distilled variant |
| Component | Node | Model | Notes |
|---|---|---|---|
| Gemma 3 | CLIPLoader (type=ltxv) | gemma_3_12B_it_fp4_mixed.safetensors | 9GB FP4, in text_encoders/ |
Loading note: The checkpoint bundles the VAE internally. The Gemma 3 text encoder loads separately. Use CLIPLoader with type: "ltxv" pointing at the text_encoders/ directory.
| LoRA | File | Purpose |
|---|---|---|
| Distilled LoRA | ltx2/ltx-2-19b-lora-camera-control-dolly-left.safetensors | Camera dolly left |
| Distilled LoRA (384) | ltx2/ltx-2-19b-distilled-lora-384.safetensors | Apply to base model for distilled behavior |
| Camera Dolly Left | ltx-2-19b-lora-camera-control-dolly-left.safetensors | Camera movement |
Located in loras/LTXV2/:
style/PLORAV7_LTX_000010500.safetensorsconcept/head_swap_v1_13500_first_frame.safetensorsconcept/LTX-2 - Better Female Nudity.safetensorsaction/LTX2-i2v-OralSuite.safetensorsaction/LTX2-i2v-SexThrust.safetensorsconcept/ and action/ subfoldersBinds text conditioning with frame rate information:
{
"class_type": "LTXVConditioning",
"inputs": {
"positive": ["<clip_text_encode>", 0],
"negative": ["<clip_text_encode_neg>", 0],
"frame_rate": 25
}
}
Creates the initial video latent (for T2V):
{
"class_type": "EmptyLTXVLatentVideo",
"inputs": {
"width": 768,
"height": 512,
"length": 97,
"batch_size": 1
}
}
Frame count constraint: Must be 8n + 1 (9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105, 113, 121).
Dedicated sigma schedule for LTX-V2 latent space:
{
"class_type": "LTXVScheduler",
"inputs": {
"steps": 8,
"max_shift": 2.05,
"base_shift": 0.95,
"stretch": true,
"terminal": 0.1
}
}
Connect the optional latent input for latent-aware shift scaling.
All-in-one node that encodes image, creates latent, and wraps conditioning:
{
"class_type": "LTXVImgToVideo",
"inputs": {
"positive": ["<conditioning>", 0],
"negative": ["<conditioning>", 0],
"vae": ["<checkpoint>", 2],
"image": ["<load_image>", 0],
"width": 768,
"height": 512,
"length": 97,
"batch_size": 1,
"strength": 0.6
}
}
{
"class_type": "LTXVLatentUpsampler",
"inputs": {
"latent": ["<sampler_output>", 0],
"upscale_model": ["<upscale_loader>", 0]
}
}
Requires LatentUpscaleModelLoader with ltx-2-spatial-upscaler-x2-1.0.safetensors.
Uses SamplerCustomAdvanced with manual sigmas, NOT standard KSampler:
| Parameter | Stage 1 (Generate) | Stage 2 (Upscale) |
|---|---|---|
| sampler | euler | euler |
| steps | 8 | 4 |
| cfg | 1.0 | 1.0 |
| scheduler | LTXVScheduler | Manual sigmas |
Stage 1 sigmas (via LTXVScheduler): max_shift=2.05, base_shift=0.95, stretch=true, terminal=0.1
Stage 2 sigmas (manual, for upscale refinement): 0.909375, 0.725, 0.421875, 0.0
| Parameter | Value |
|---|---|
| sampler | res_2s |
| steps | 20 |
| cfg | 4.0 |
| scheduler | LTXVScheduler |
| distilled_lora_strength | 0.6 |
| Aspect | Stage 1 | After 2x Upscale | Notes |
|---|---|---|---|
| 3:2 landscape | 768x512 | 1536x1024 | Default |
| 16:9 landscape | 960x544 | 1920x1088 | Official example |
| 1:1 square | 640x640 | 1280x1280 | |
| 4:3 landscape | 704x512 | 1408x1024 |
Start at lower resolution for Stage 1 to manage VRAM, then upscale.
8n + 1)| Frames | Duration @25fps | Duration @24fps | Notes |
|---|---|---|---|
| 49 | 1.96s | 2.04s | Quick test |
| 81 | 3.24s | 3.38s | Short clip |
| 97 | 3.88s | 4.04s | Default |
| 121 | 4.84s | 5.04s | Official example, recommended |
| 161 | 6.44s | 6.71s | Longer clip |
| 257 | 10.28s | 10.71s | Maximum |
Standard: 25 fps (conditioned via LTXVConditioning). 24 and 30 fps also supported.
CheckpointLoaderSimple → MODEL + VAE
CLIPLoader (ltxv, gemma_3_12B_it_fp4_mixed) → CLIP
├─ CLIPTextEncode (positive) → CONDITIONING
└─ CLIPTextEncode (negative) → CONDITIONING
LTXVConditioning (positive, negative, frame_rate=25) → pos/neg CONDITIONING
EmptyLTXVLatentVideo (768x512, 121 frames) → LATENT
LTXVScheduler (steps=8, max_shift=2.05, base_shift=0.95) → SIGMAS
SamplerCustomAdvanced (model, sigmas, positive, negative, latent)
→ Stage 1 LATENT
[Optional: LTXVLatentUpsampler → 2x LATENT → SamplerCustomAdvanced Stage 2]
VAEDecode (or LTXVSpatioTemporalTiledVAEDecode for VRAM savings) → IMAGE
VHS_VideoCombine (or CreateVideo + SaveVideo) → MP4
{
"1": { "class_type": "CheckpointLoaderSimple", "inputs": { "ckpt_name": "ltx-2-19b-distilled.safetensors" }},
"2": { "class_type": "CLIPLoader", "inputs": { "clip_name": "gemma_3_12B_it_fp4_mixed.safetensors", "type": "ltxv" }},
"3": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "<positive prompt>" }},
"4": { "class_type": "CLIPTextEncode", "inputs": { "clip": ["2", 0], "text": "" }},
"5": { "class_type": "LTXVConditioning", "inputs": {
"positive": ["3", 0], "negative": ["4", 0], "frame_rate": 25
}},
"6": { "class_type": "EmptyLTXVLatentVideo", "inputs": {
"width": 768, "height": 512, "length": 121, "batch_size": 1
}},
"7": { "class_type": "LTXVScheduler", "inputs": {
"steps": 8, "max_shift": 2.05, "base_shift": 0.95,
"stretch": true, "terminal": 0.1, "latent": ["6", 0]
}},
"8": { "class_type": "KSamplerSelect", "inputs": { "sampler_name": "euler" }},
"9": { "class_type": "SamplerCustomAdvanced", "inputs": {
"model": ["1", 0],
"positive": ["5", 0],
"negative": ["5", 1],
"sigmas": ["7", 0],
"latent_image": ["6", 0],
"noise": ["10", 0],
"sampler": ["8", 0],
"guider": ["11", 0]
}},
"10": { "class_type": "RandomNoise", "inputs": { "noise_seed": 42 }},
"11": { "class_type": "CFGGuider", "inputs": {
"model": ["1", 0],
"positive": ["5", 0],
"negative": ["5", 1],
"cfg": 1.0
}},
"12": { "class_type": "VAEDecode", "inputs": { "samples": ["9", 0], "vae": ["1", 2] }},
"13": { "class_type": "VHS_VideoCombine", "inputs": {
"images": ["12", 0], "frame_rate": 25, "loop_count": 0,
"filename_prefix": "ltxv2", "format": "video/h264-mp4",
"pingpong": false, "save_output": true,
"pix_fmt": "yuv420p", "crf": 19, "save_metadata": true, "trim_to_audio": false
}}
}
Alternative simple output (built-in nodes instead of VHS):
{
"12": { "class_type": "VAEDecode", "inputs": { "samples": ["9", 0], "vae": ["1", 2] }},
"13": { "class_type": "CreateVideo", "inputs": { "images": ["12", 0], "fps": 25 }},
"14": { "class_type": "SaveVideo", "inputs": { "video": ["13", 0], "filename_prefix": "video/ltxv2", "format": "auto", "codec": "auto" }}
}
Seven official camera control LoRAs from Lightricks:
| Movement | LoRA File |
|---|---|
| Dolly Left | ltx-2-19b-lora-camera-control-dolly-left.safetensors |
| Dolly Right | ltx-2-19b-lora-camera-control-dolly-right.safetensors |
| Dolly In | ltx-2-19b-lora-camera-control-dolly-in.safetensors |
| Dolly Out | ltx-2-19b-lora-camera-control-dolly-out.safetensors |
| Jib Up | ltx-2-19b-lora-camera-control-jib-up.safetensors |
| Jib Down | ltx-2-19b-lora-camera-control-jib-down.safetensors |
| Static | ltx-2-19b-lora-camera-control-static.safetensors |
Usage: Apply with LoraLoaderModelOnly at strength 1.0. Do NOT describe camera movement in your prompt — the LoRA handles it.
{
"class_type": "LoraLoaderModelOnly",
"inputs": {
"model": ["<checkpoint>", 0],
"lora_name": "ltx-2-19b-lora-camera-control-dolly-left.safetensors",
"strength_model": 1.0
}
}
Cannot combine camera control LoRA with IC-LoRA (canny/depth/pose) in the same generation.
Apply with LoraLoaderModelOnly. Typical strength: 0.5–1.0.
{
"class_type": "LoraLoaderModelOnly",
"inputs": {
"model": ["<checkpoint_or_camera_lora>", 0],
"lora_name": "LTXV2\\concept\\LTX-2 - Better Female Nudity.safetensors",
"strength_model": 0.8
}
}
Concept/style LoRAs CAN be stacked with camera control LoRAs.
| Config | VRAM | Notes |
|---|---|---|
| bf16 checkpoint + FP4 Gemma | ~24GB+ | Tight on RTX 4090, may OOM |
| FP8 checkpoint + FP4 Gemma | ~16-20GB | Recommended for 24GB GPUs |
| bf16 + tiled VAE decode | ~22GB | Use LTXVSpatioTemporalTiledVAEDecode |
VRAM warnings from MEMORY.md: "LTXV2 can OOM on 24GB — suggest FP8 quantized models or --lowvram"
VAEDecodeTiled or LTXVSpatioTemporalTiledVAEDecode instead of standard VAEDecodeclear_vram before switching to LTX-V2 from another model familyNatural language descriptions. Be specific about motion, camera angles, and temporal progression:
Good: "A woman with flowing auburn hair walks through a sun-dappled forest, leaves falling gently around her, soft golden hour lighting, cinematic depth of field"
Bad: "woman, forest, walking"
Describe the entire scene progression, not just a single moment. Include lighting, mood, and motion cues.
For production quality, generate at low resolution then upscale:
LTXVLatentUpsampler (2x spatial) → 1536x1024This requires the spatial upscaler model: ltx-2-spatial-upscaler-x2-1.0.safetensors (place in models/latent_upscale_models/).