ltx2-5

WeeLLM runs large diffusion models with as little as 4 GB of VRAM, without any quantization. It dynamically determines how many layers can fit within the available VRAM and streams the text encoder and transformer layers to the GPU layer by layer, enabling inference on hardware with limited VRAM. It supports both safetensors and GGUF models.

LTX 2.5 serverless worker template with i2v t2v workflows and bundled frontend.

Prompt-writing skill for LTX-2.5 text-to-video generation (6-element method)

A local, self-hosted AI film and design studio. Write a screenplay with a local LLM, render scenes with MiniMax H3, LTX and Wan through ComfyUI, cut them on a full timeline, paint and compose in a layered image editor, sketch and model in CAD (constrained sketches and parametric 3D bodies), and bring in scenes from Blender and Unreal Engine