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| Ltx 2 training-inference pipeline(Ref- Reaserch Paper) |
Installation
1. Install ComfyUI if you are a new user. Older user need to update it from the Manager by selecting Update All.
2. From the Manager, select Install Custom Nodes option. Search for "LTXVideo" custom node and install it. If already installed then just update it from the Manager by clicking on Custom nodes manager option.
3. Now, there are different model variants-text to video, Image to video and Control to video from Ltx -2 hugging face repository. Download any of them as described below:
| Sl No. | Model Name | Short Description |
|---|---|---|
| 1 | LTX-2 19B Dev FP8 (ltx-2-19b-dev-fp8.safetensors) |
Development version of the LTX-2 19B model optimized with FP8 precision. It reduces VRAM usage and improves inference speed while maintaining near-original output quality. Best suited for experimentation and faster local inference. |
| 2 | LTX-2 19B Dev BF16 (ltx-2-19b-dev.safetensors) |
Full development model using BF16 precision. Requires 16GB VRAM with 32GB system RAM. Offers higher numerical stability and better output consistency compared to FP8, making it ideal for high-quality generation, testing, and fine-tuning workflows. |
| 3 | LTX-2 19B Distilled FP8 (ltx-2-19b-distilled-fp8.safetensors) |
A distilled and compressed version of the LTX-2 19B model using FP8 precision. Designed for faster inference and lower hardware requirements while preserving most of the core model capabilities. Suitable for resource-constrained environments. |
| 4 | LTX-2 19B Distilled BF16 (ltx-2-19b-distilled.safetensors) |
Distilled variant of the LTX-2 19B model in BF16 format. Balances reduced model size with better output stability and quality compared to FP8 distilled versions. Ideal for production-oriented inference where quality still matters. |
Save it into ComfyUI/models/checkpoints folder, not the diffusion_models folder.
GGUF- If you want the LTX-2 GGUF models for low VRAMs, download them and setup accordingly. Make sure you have already installed the ComfyUI-GGUF custom nodes by city-96 from the Manager. If already done, update this custom nodes from the Manager.
(a) LTXV-2 GGUF by Kijai
(b) LTXV-2 GGUF by Quantstack
(c) LTXV-2 GGUF by Unsloth
Save it into ComfyUI/models/unet folder.
3. Download upscaler models provided below.
(a) Spatial upscaler (ltx-2-spatial-upscaler-x2-1.0.safetensors)
(b) Temporal Upscaler (ltx-2-temporal-upscaler-x2-1.0.safetensors)
Save them into ComfyUI/models/latent_upscale_models folder.
4. Download ltx-2-19b-distilled-lora model (ltx-2-19b-distilled-lora-384.safetensors). Save it inside ComfyUI/models/loras folder.
5. Download Quantized Gemma text encoder (gemma-3-12b-it-qat-q4_0-unquantized). Save it inside ComfyUI/models/text_encoders/gemma-3-12b-it-qat-q4_0-unquantized folder.
6. Now, if you want LTX Control nets (Canny, Pose,Depth, Dolly,static etc) lora models. Then, download them as provided below:
| Sl No. | Model Name | Download Link |
|---|---|---|
| 1 | ltx-2-19b-ic-lora-detailer.safetensors | Download |
| 2 | ltx-2-19b-ic-lora-pose-control.safetensors | Download |
| 3 | ltx-2-19b-ic-lora-canny-control.safetensors | Download |
| 4 | ltx-2-19b-ic-lora-depth-control.safetensors | Download |
| 5 | ltx-2-19b-lora-camera-control-dolly-in.safetensors | Download |
| 6 | ltx-2-19b-lora-camera-control-dolly-left.safetensors | Download |
| 7 | ltx-2-19b-lora-camera-control-dolly-out.safetensors | Download |
| 8 | ltx-2-19b-lora-camera-control-dolly-right.safetensors | Download |
| 9 | ltx-2-19b-lora-camera-control-jib-down.safetensors | Download |
| 10 | ltx-2-19b-lora-camera-control-jib-up.safetensors | Download |
| 11 | ltx-2-19b-lora-camera-control-static.safetensors | Download |
Save them inside ComfyUI/models/loras folder.
7. Restart and refresh ComfyUI.
Workflows
1. The workflow can be found inside ComfyUI/custom_nodes/ComfyUI-LTXVideo/example_workflows folder. You can also get it by navigating from the ComfyUI templates section.
LTX-2_I2V_Distilled_wLora.json
LTX-2_I2V_Full_wLora.json
LTX-2_ICLoRA_All_Distilled.json
LTX-2_T2V_Distilled_wLora.json
LTX-2_T2V_Full_wLora.json
LTX-2_V2V_Detailer.json
We used RTX 4080 super with 16GB VRAM to generate a 5.4 seconds t2v long 480p video that took around 2 minutes.
2. Drag and Drop into ComfyUI.
Settings-
BF16 full variant: CFG-3, Steps- 25
Distilled variant: CFG-1; Steps-8
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