Model reference · open weights
LTX-Video-0.9.8 is an open-weight video model from Lightricks. LTX-Video-0.9.8-13B-distilled (BF16) weighs 92.8 GB; the smallest configuration that runs it is H100 80 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the Lightricks/LTX-Video-0.9.8-13B-distilled model card, 2026-10-01
What it is
| Released by | Lightricks |
|---|---|
| Released | 2025-07-17 |
| Parameters | 13.0B |
| VRAM | 92.8 GB for the weights |
What it runs on
| Card | Weights | Memory |
|---|---|---|
| RTX 3060 12 GB … L40S 48 GB | does not fit | |
| A100 80 GB | fits (encoders offloaded) | 78.2 GB |
| H100 80 GB | fits (encoders offloaded) | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | tight | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | tight | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
This model card focuses on the model associated with the LTX-Video model, codebase available here.
LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 30 FPS videos at a 1216×704 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content.
| Name | Notes | inference.py config | ComfyUI workflow (Recommended) |
|---|---|---|---|
| ltxv-13b-0.9.8-dev | Highest quality, requires more VRAM | ltxv-13b-0.9.8-dev.yaml | ltxv-13b-i2v-base.json |
| ltxv-13b-0.9.8-mix | Mix ltxv-13b-dev and ltxv-13b-distilled in the same multi-scale rendering workflow for balanced speed-quality | N/A | ltxv-13b-i2v-mixed-multiscale.json |
| ltxv-13b-0.9.8-distilled | Faster, less VRAM usage, slight quality reduction compared to 13b. Ideal for rapid iterations | ltxv-13b-0.9.8-distilled.yaml | ltxv-13b-dist-i2v-base.json |
| ltxv-2b-0.9.8-distilled | Smaller model, slight quality reduction compared to 13b distilled. Ideal for light VRAM usage | ltxv-2b-0.9.8-distilled.yaml | N/A |
| ltxv-13b-0.9.8-fp8 | Quantized version of ltxv-13b | ltxv-13b-0.9.8-dev-fp8.yaml | ltxv-13b-i2v-base-fp8.json |
| ltxv-13b-0.9.8-distilled-fp8 | Quantized version of ltxv-13b-distilled | ltxv-13b-0.9.8-distilled-fp8.yaml | ltxv-13b-dist-i2v-base-fp8.json |
| ltxv-2b-0.9.8-distilled-fp8 | Quantized version of ltxv-2b-distilled | ltxv-2b-0.9.8-distilled-fp8.yaml | N/A |
| ltxv-2b-0.9.6 | Good quality, lower VRAM requirement than ltxv-13b | ltxv-2b-0.9.6-dev.yaml | ltxvideo-i2v.json |
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. Runs as it is with diffusers, on the machine, in Python.
# on your rented machine: pip install diffusers transformers accelerate ftfy
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import export_to_video
pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video-0.9.8-13B-distilled", torch_dtype=torch.bfloat16).to("cuda")
frames = pipe(prompt="a drone shot over a forest at sunrise").frames[0]
export_to_video(frames, "/workspace/out.mp4", fps=16)