mlc-ai/web-stable-diffusion

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3721 stars · 238 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A project that compiles and runs Stable Diffusion text-to-image models entirely inside web browsers using WebGPU and WebAssembly, with no server-side inference. It provides a Python-first MLC/TVM-based workflow for optimizing and deploying the models to the browser.

Use cases

• generate images from text prompts in the browser
• run stable diffusion locally without a GPU server
• build privacy-preserving client-side AI image generation web apps
• reduce inference hosting costs by offloading compute to the client
• experiment with WebGPU machine learning in the browser
• compile and optimize diffusion models for web deployment

When to choose

• you want fully client-side text-to-image generation with no backend
• privacy matters and prompts/images should never leave the user's device
• you want to cut server GPU costs for image generation
• you're building a WebGPU/WebAssembly ML demo or web app

When to avoid

• you need broad browser support - WebGPU is not universally available
• you need the fastest or highest-quality generation on powerful server GPUs
• you need a production-ready, actively evolving stable diffusion toolkit
• your target users have low-end devices with limited memory

Facets

library · maturity maintenance

machine-learning deep-learning image-processing gpu-computing compiler artificial-intelligence image-processing web-development deep-learning browser wasm python webgpu stable-diffusion text-to-image webassembly tvm client-side-inference mlc web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="mlc-ai/web-stable-diffusion")