README.md

metadata

license: other
license_name: ltx-2-community-license-agreement
license_link: https://huggingface.co/Lightricks/LTX-2.3/blob/main/LICENSE
language:
  - en
tags:
  - text-to-video
  - image-to-video
  - audio-to-video
  - ltx-video
  - gguf
  - quantized
  - distilled
  - dit
base_model: Lightricks/LTX-2.3
pipeline_tag: text-to-video

LTX-Video 2.3 (v1.1) 22B Distilled - GGUF

This repository contains the LTX-Video 2.3 (v1.1) Distilled weights, quantized to GGUF format.

GGUF offers highly efficient inference and excellent memory scaling, allowing you to run this heavy 22B parameter model on consumer hardware by splitting the workload between your GPU (VRAM) and CPU (System RAM).

⚡ Model Details

• Architecture: LTX-Video 2.3 22B Distilled(v1.1)
• Parameter Count: ~22B
• Format: GGUF
• Special Feature: Native Audio-Visual generation (DiT-based)

📦 Available Quantizations

Choose the version that best fits your system's memory constraints.

• LTX-2.3-22B-distilled-1.1-Q8_0.gguf (25.5 GB): Highest quality, nearly indistinguishable from unquantized. Requires significant RAM/VRAM.
• LTX-2.3-22B-distilled-1.1-Q6_K.gguf (21.0 GB): Excellent balance of quality and size. Recommended for high-end GPUs.
• LTX-2.3-22B-distilled-1.1-Q5_K_M.gguf (19.4 GB): Very good quality with a smaller footprint.
• LTX-2.3-22B-distilled-1.1-Q4_K_M.gguf (17.8 GB): The standard recommendation for most users. Great trade-off between performance and visual fidelity.
• LTX-2.3-22B-distilled-1.1-Q3_K_M.gguf (14.7 GB): Smallest footprint. Best for machines with limited memory, though minor visual degradation may occur.

🛠️ Usage & Implementation (ComfyUI)

To use these GGUF files in ComfyUI, you will need a custom node suite that supports loading GGUF models (such as ComfyUI-GGUF).

📜 License

This model is released under the LTX-2 Community License Agreement by Lightricks.