onediff is a Coding & Development tool that accelerates diffusion models. It provides out-of-the-box acceleration for popular UIs/libraries like HF diffusers and ComfyUI, significantly speeding up model inference.
onediff is an out-of-the-box acceleration library designed for diffusion models, offering significant speed improvements for various applications. It provides optimized GPU kernels and PyTorch code compilation tools, making it compatible with popular interfaces and libraries such as Hugging Face Diffusers and ComfyUI. The library supports a wide range of state-of-the-art models including SD 1.5-2.1, SDXL, SDXL Turbo, and Stable Video Diffusion, along with algorithms like LoRA and ControlNet. onediff is particularly useful for production environments, featuring capabilities to avoid compilation time for new input shapes and online serving, and supports distributed inference. An enterprise solution is also available for even greater performance gains and dedicated technical support.
Best used for
Ideal for developers who need to significantly speed up diffusion model inference, optimize PyTorch code for GPU performance, and deploy accelerated models in production environments. Especially valuable for those working with Stable Diffusion, Stable Video Diffusion, and other state-of-the-art generative AI models.
What types of diffusion models does onediff accelerate?
onediff supports acceleration for a wide range of state-of-the-art diffusion models, including SD 1.5-2.1, SDXL, SDXL Turbo, and Stable Video Diffusion. It also accelerates algorithms like LoRA, ControlNet, and InstantID, ensuring broad compatibility for various generative AI tasks.
Can onediff be used with existing Stable Diffusion UIs?
Yes, onediff provides out-of-the-box acceleration for popular user interfaces and libraries. This includes seamless integration with Hugging Face Diffusers, ComfyUI, and Stable Diffusion web UI, allowing users to easily enhance their existing workflows.
What are the system requirements for using onediff?
onediff primarily supports Linux operating systems and is compatible with NVIDIA GPUs such as 3090 RTX, 4090 RTX, A100, A800, and A10. While Windows is not directly supported, it can be used under WSL (Windows Subsystem for Linux) for compatibility.