SWE-agent 1.0 is the open-source SOTA on SWE-bench Lite! Tons of new features: massively parallel runs; cloud-based deployment; extensive configurability with tool bundles; new command line interface & utilities.

Completing games requires long context and complex visual processing- so we put a bunch of 90s games into an emulator and made a benchmark. Our agent can't even the first level of these games. You can download it right now and try it out.

Can GPT, Claude, and Gemini play video games like Zelda, Civ, and Doom II? 𝗩𝗶𝗱𝗲𝗼𝗚𝗮𝗺𝗲𝗕𝗲𝗻𝗰𝗵 evaluates VLMs on Game Boy & MS-DOS games given only raw screen input, just like how a human would play. The best model (Gemini) completes just 0.48% of the benchmark! 🧵👇

AlgoBench is extremely tough, with agents not finding substantial speedups on most tasks. But sometimes these agents do really cool things: here, the agent realized that it could solve this convex optimization problem with a scipy function, leading to an 81x speedup.

Excited to release AlgoTune!! It's a benchmark and coding agent for optimizing the runtime of numerical code 🚀 algotune.io 📚 algotune.io/paper.pdf 🤖 github.com/oripress/AlgoT… with Ofir Press Ori Press Patrick Kidger Bartolomeo Stellato Arman Zharmagambetov & many others 🧵

Congrats to my brother Dr. Ori Press on passing his PhD defense! Ori Press

We just benchmarked Qwen 3 Coder and GLM 4.5 on AlgoTune, and they manage to beat Claude Opus 4! We're excited to see if the models that will be released this week manage to make progress. Also: I just defended my PhD and I'm on the industry job market, my DMs are open :)

We know that a bunch of teams are working on applying AlphaEvolve to AlgoTune, super excited to see some initial results! This is going to get super interesting.

Just added Claude Opus 4.1 and gpt-oss-120b to the AlgoTune leaderboard. Excited to see if GPT-5 can break the 2 barrier!

Introducing OpenEvolve x AlgoTune! Now you can run and benchmark evolutionary coding agents on 100+ algorithm optimization tasks from algotune.io

What if your agent uses a different LM at every turn? We let mini-SWE-agent randomly switch between GPT-5 and Sonnet 4 and it scored higher on SWE-bench than with either model separately. Read more in the SWE-bench blog 🧵