#88th of 30 in Image and videoFor image, video and design, video and animation
ltx-2
Text and image to video model with synchronized audio, plus pipelines and trainer
- Stars
- 9.8k
- License
- custom license
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
5,372 on 1 Apr 20269,834 on 21 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
LTX-2 is a 22B-parameter DiT model from Lightricks that generates video with synchronized audio from text, images or input audio. The repo is a Python monorepo with ltx-core, ltx-pipelines (distilled, DFR, two-stage, retake, IC-LoRA, HDR, dubbing) and ltx-trainer for LoRA and full fine-tuning. Weights are downloaded separately from Hugging Face, about 66 GiB for the quick-start set.
Who it is for: Engineers running or fine-tuning open video generation models on CUDA GPUs
Ranked among open-source alternatives to Midjourney (#8 of 10).
Strengths
- Generates audio and video together in one model, including speech
- Many pipelines: distilled, DFR, keyframe, audio-to-video, retake, HDR/EXR, dubbing
- Includes a trainer for LoRA, full fine-tuning and IC-LoRA
- FP8 quantization and CPU or disk offload flags for limited GPU memory
Weaknesses
- Quick-start weights are about 66 GiB and gated behind Hugging Face terms
- Exact VRAM requirements are not stated in the README
- License is not identified by tooling (NOASSERTION); check the repo terms
- Fastest VAE backend (natten) is Linux and CUDA only; CLI-driven, no built-in UI
What it needs
- GPU required
- Needs uv, Hugging Face CLI, PyTorch, CUDA
- Models: LTX-2.5 22B distilled, LTX-2.5 22B dev, LTX-2.3, Gemma 4 12B text encoder, safetensors
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