cumulo-autumn/StreamDiffusion

Health v2 · maintenance only

Adoption not part of the score

10806 stars · 834 forks observed · 2026-08-28

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

StreamDiffusion is a Python pipeline for real-time interactive diffusion-based image generation, achieving 100+ fps on modern GPUs. It optimizes the standard Stable Diffusion pipeline with stream batching, residual classifier-free guidance, similarity filtering, and KV-cache pre-computation.

Use cases

• generate images in real time from text prompts
• run interactive img2img generation from a webcam feed
• build a live visual effect tool with stable diffusion
• speed up stable diffusion inference to 100 fps
• create real-time AI art installations

When to choose

• you need low-latency, high-fps diffusion image generation
• you want to build interactive real-time AI image applications on a strong GPU
• you want an optimized alternative to the standard diffusers pipeline

When to avoid

• you lack a modern NVIDIA GPU
• you need maximum image quality over speed
• you need a general-purpose diffusion library rather than a real-time pipeline

Facets

library · maturity active

image-processing machine-learning deep-learning gpu-computing stable-diffusion image-processing deep-learning gpu-computing python windows diffusion-pipeline real-time-generation stable-diffusion txt2img img2img pytorch real-time gpu linux macos

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