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Benchmarks · agentic

VitaBench

Can an agent finish a real-life errand that spans food delivery, restaurant bookings and travel — 66 tools, a customer whose wishes shift mid-conversation, and no domain policy to lean on? Maintained by Meituan LongCat team. Score: Cross-Scenarios Avg @4 on the 100 cross-scenario tasks (the paper's main result), graded by the benchmark's rubric-based sliding-window LLM evaluator; the page does not define @4 in words — by the column name it is the average over four trials.

12 models · 14 results · data as of 2026-10-29 · vitabench.github.io ↗

Leaderboard

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12 of 12 selected
Gemini 3 Flash high

All results

14 rows
#ModelEffortVitaBench
1Gemini 3 Flashhigh32.5%
2Gemini 3 Prohigh31.5%
3Gemini 3 Prolow30.0%
4o3high26.3%
5GPT-5.2xhigh24.3%
6DeepSeek V3.2high24.0%
7o4 minihigh19.5%
8GLM 4.7none18.3%
9Qwen 3 235B-A22Bxhigh14.5%
10Qwen 3 Maxmax14.3%
11Kimi K2medium12.8%
12Kimi K2.090511.5%
13Qwen 3 32Bnone5.3%
14GPT-5.2none0.8%