KAT Claw Bench
KAT-Coder-Pro V2.5 85.5% In use Agents complete business tool-use tasks from Kuaishou internal agent needs in seven categories, such as office work, content operations, data analysis and monitoring. Automatic checks grade objective outputs, and model and human review grade open deliverables.
In-house Claw-style benchmark described in the KAT-Coder-V2.5 tech report.
Made by Kuaishou (KwaiKAT team) Released Jul 2026 General assistants Tasks kept private Last in a launch post Jul 2026
Last model added Jul 2026
- Level
- University Undergraduates and entry-level professionals
- Scored
- Graded by a model A language model scores each response, usually against a rubric.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
1
Model scored in lab cards
1
Launch post lists it, from 1 lab
KAT-Coder-Pro V2.5 leads with 85.5%
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.
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | KAT-Coder-Pro V2.5 | 85.5% | Jul 2026 | Model card |
The best score passed 85% in Jul 2026
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
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.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 6 Jul 2026 | KAT-Coder-Pro V2.5 | 85.5 | KAT Claw Bench |
More in Tool use
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Muse Spark 1.1 88.1% - BFCL V4 In use Models call functions and tools, including multi-turn agentic tasks with web search and memory. Checked against expected calls and outcomes.
Qwen3.7-Max 75% - τ³-bench Banking In use Agents act as banking customer-service reps over many turns with a simulated user, following policy. Pass^1 on the final database state. Qwen 3.8 Max 55.1%
- Claw-Eval In use 300 human-verified agent tasks (service orchestration, multimodal, multi-turn dialogue) audited via traces and snapshots. Rubric scores with Pass^3 consistency. Claude Sonnet 4.6 81.4%
- DeepSearchQA In use Questions that need multi-step search and synthesis. Final answers graded against references. Kimi K3 95%