KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments

Summary

<p>The KwaiKAT Team at Kuaishou has published the KAT-Coder-V2.5 technical report, arguing that agentic coding capability is bottlenecked by training infrastructure rather than model scale. AutoBuilder raised environment construction success from 16.5% to 57.2%, producing over 100,000 verifiable environments across 12 languages, while a sandbox audit cut RL feedback errors from roughly 16% to below 2%.</p> <p>The post <a href="https://www.marktechpost.com/2026/07/26/kwaikat-team-releases-kat-coder-v2-5-an-agentic-coding-model-trained-on-100000-verifiable-repository-environments/">KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>