Video Runtime
Developer-onlyLive TransformationOfficial source

StreamDiffusion

Transform webcam and screen frames with an accelerated diffusion pipeline for interactive visuals.

Access and release status are source-checked descriptions, not a live uptime check. A reachable website does not establish that video playback or interaction currently works.

View GitHub ↗

No rights-cleared product preview yet. See the official page for its latest interface.

Published by Video Runtime · Source check 2026-09-05 · Evidence method · Suggest a correction

EDITORIALLY VERIFIED PRODUCT INFORMATION

About StreamDiffusion

Transform webcam and screen frames with an accelerated diffusion pipeline for interactive visuals. Batches work across denoising steps and skips similar inputs to reduce repeated computation.

Key features

Includes browser examples for webcam and screen input, useful starting points for creative tools.

Getting started

Open the official repository, read its current README and licence, then follow the documented environment, checkpoint and inference steps. Start with the supplied example before using your own media or data.

Real-time interaction

Batches work across denoising steps and skips similar inputs to reduce repeated computation.

Pricing

Apache-2.0; compute costs extra Repository code: Apache-2.0. Model weights and dependencies may have separate terms. No hosted price is estimated here. Budget for your own GPU or cloud usage after testing a representative workload.

Limitations

This is primarily an image diffusion pipeline applied to frames, not a native video model with guaranteed temporal consistency.

Read the documentation ↗

EDITORIAL VIEW

Editor's Verdict

Consider StreamDiffusion if its documented workflow matches your experiment; start from the linked repository rather than an unofficial mirror.

Check the licence and run a small local evaluation before choosing it for production. No ratings or measured results are inferred from its publication.

How It Works

  • Batches work across denoising steps and skips similar inputs to reduce repeated computation.

What We Like

  • Includes browser examples for webcam and screen input, useful starting points for creative tools.

Current Limitations

  • This is primarily an image diffusion pipeline applied to frames, not a native video model with guaranteed temporal consistency.

Pricing & Access

  • Repository code: Apache-2.0. Model weights and dependencies may have separate terms.
  • No hosted price is estimated here. Budget for your own GPU or cloud usage after testing a representative workload.

Verification Summary

  • Official repository and licence reviewed on 2026-09-05. Video Runtime has not installed or benchmarked this project.
  • This is a source review, not verification of demo uptime, output quality or performance on your hardware.
Technical notes & official performance

Official Performance Data

  • Authors publish frame-throughput benchmarks on an RTX 4090. These are configuration-specific image pipeline results, not measured camera-to-display latency.

Technical Notes

  • The repository documents TensorRT acceleration and SD-Turbo or LCM-based configurations.

Sources

  1. Official GitHub repository ↗github · accessed 2026-09-05
  2. Code licence ↗github · accessed 2026-09-05

Access, stage & mechanism

These are separate source-checked facts, not a live uptime monitor. Unverified fields are left open; transport and persistent sessions do not establish how frames are generated.

Release stage
Not verified
Access mode
Not verified
Source availability
Not verified
Transport
Not verified
Interaction
Not verified
Session mode
Not verified
Generation mechanism
Not verified
Continuity method
Not verified
Licence status
Not verified
Tasks
Not classified

Read how official-source and hands-on records stay separate in our Methodology.