KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments
The KwaiKAT Team at Kuaishou has released KAT-Coder-V2.5, an agentic coding model trained on over 100,000 verifiable repository environments spanning 12 programming languages. Their AutoBuilder tool increased environment construction success rates from 16.5% to 57.2%, and a sandbox audit reduced RL feedback errors from approximately 16% to below 2%.
Why it matters: This release highlights the importance of scaling training infrastructure for verifiable environments to improve agentic coding performance, rather than relying solely on increasing model size.
Full story at: MarkTechPost / AI ↗