Benchmark Almanac

KAT Code Bench

Agents turn a natural-language requirement into a patch in a real repository drawn from Kuaishou internal development work. Each task pins its commit, environment and an executable verification entry point across 12 languages.

In-house benchmark described in the KAT-Coder-V2.5 tech report. It covers bug fixes, feature work, compatibility and cross-module edits.

Made by Kuaishou (KwaiKAT team) Released Jul 2026 Fixing real repositories Tasks kept private Last in a launch post Jul 2026 Last model added Jul 2026
Level
University Undergraduates and entry-level professionals
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Agent task Many steps in a terminal, browser, desktop, app, game or robot.
2
Models scored in lab cards
2
Launch posts list it, from 1 lab

KAT-Coder-Pro V2.5 leads with 53.1%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 KAT-Coder-Pro V2.5 53.1%
  2. 2 KAT-Coder-V2.5-Dev 46.2%
#ModelScoreSettingDateSource
1 KAT-Coder-Pro V2.5 53.1% Jul 2026 Model card
2 KAT-Coder-V2.5-Dev 46.2% Jul 2026 Model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% Near the ceiling (85%) KAT-Coder-Pro V2.5 0% 20% 40% 60% 80% 100% Near the ceiling (85%) KAT-Coder-Pro V2.5

One lab put it in a launch post in the last six months

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

Kuaishou
DateLaunch postScoreAs the post writes it
23 Jul 2026 KAT-Coder-V2.5-Dev 46.2 KAT-Code-Bench
6 Jul 2026 KAT-Coder-Pro V2.5 53.1 KAT Code Bench

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  • DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
  • SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases. Seed2.1 Pro 59.8%
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