One UI is all done with chatgpt web, midjourney, gpts,suno,luma,runway,viggle,flux,ideogram,realtime,pika,udio; Simultaneous support Web / PWA / Linux / Win / MacOS platform
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.
Train LoRAs for Qwen-Image 2.1, FLUX.2 Klein 9B, FLUX.3 Image Klein, Krea 2, Z-Image, MOSS-Image, ERNIE-Image, Ideogram 4, Anima, SDXL (Pony, Illustrious, NoobAI), LTX 2.3, MiniMax-H3, and more on NVIDIA GPUs from 4–8 GB VRAM. One install, one launcher, NF4 models. Windows, Linux and RunPod.
On-device ComfyUI style node graph for image/video diffusion models on Android. Local SD1.5, SDXL, Flux, Z-image, Anima, Qwen Image 2.1, Krea 2, MOSS Image, Ideogram 4, inpainting, outpainting, controlnet, LoRA, IPAdapter, auto-segment and WAN 2.2 5B video on the Qualcomm Hexagon NPU. Fully offline, no server, no account.