OpenRSI Foundation

We scaled Recursive Self-Improvement (RSI) to production AI infrastructure with SGLang-Omni, shipping 14 upstream-merged PRs across 8 speech & omni models with 7.6%–344.3% throughput gains.

Blog: index.openrsi.foundation/blog/2026/open…

🚀 A milestone for OpenRSI: 3 OpenRSI agent-generated optimizations have been merged upstream into SGLang-Omni!

All three PRs underwent rigorous maintainer code review and verification by the SGLang-Omni team.

😉 Real code. Proven improvements. Lasting impact for the open-source community. More to come!

👏 Huge thanks to @zhuofengli96475 and @GenAI_is_real for leading this effort, and to the SGLang team @sgl_project for their support and collaboration!

Try OpenRSI harness now: github.com/OpenRSI-Founda…

As AI systems enter a recursive self-improvement loop, the central question is whether it can systematically move beyond human-designed methods to genuinely extend the scientific and intelligence frontier.

What’s missing is a neutral, open standard for evaluating these capabilities in real, production-scale intelligence development.

Today, we’re releasing OpenRSI-Index v0.1: evaluating whether AI can recursively improve itself and push the boundaries of intelligence and science, on production-scale clusters with 1k GPUs.

We turn fully open-source projects into autoresearch environments, with agent trajectories lasting 60+ hours. Building v0.1 took 100K+ H100-hours.

We’re building an ecosystem with and for the research community: let RSI benefit everyone, and let everyone shape RSI together.

We invite task contributors and compute partners to build this open benchmark with us - all contributors will be included as paper authors.
Shape RSI with us:
🌐 Website: index.openrsi.foundation/index.html
🛠️ GitHub: github.com/OpenRSI-Founda…
🤝 Contribute: github.com/OpenRSI-Founda…