Progress in RL for Long-Horizon SWE Tasks
billyuchenlin · x · 2026-07-15
The author shares their work on reinforcement learning for long-horizon SWE tasks, describing the process as "fun and challenging," while noting that the model demonstrates strong generalization across various settings and benchmarks.
The post also references a relevant leaderboard where Grok 4.5 ranks 2nd on FrontierSWE, trailing only Claude Fable 5 and beating out Opus 4.8, GPT-5.5, and GLM-5.2.
This update highlights two main takeaways:
- First, RL training for long-horizon software engineering tasks remains a highly worthwhile investment.
- Second, a clearer competitive landscape for agent / SWE benchmarks is emerging around these complex evaluations.
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