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reasoning benchmark

TAU3-Bench

TAU3-Bench is a benchmark for evaluating general-purpose agent capabilities, testing models on multi-turn interactions with simulated user models, retrieval, and complex decision-making scenarios.

Updated Aug 11, 2026

Models5
Model coverage5
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

TAU3-Bench Ranking

Higher score ranks better on this benchmark.

5 rows
Columns

Show columns

1XIMiMo-V2.5-ProXiaomi72.9%100.0%5CAug 11, 2026
2ACQwen3.6 PlusAlibaba Cloud / Qwen Team70.7%75.0%5CAug 11, 2026
3ZAGLM-5.1Zhipu AI70.6%50.0%5CAug 11, 2026
4ACQwen3.6-35B-A3BAlibaba Cloud / Qwen Team67.2%25.0%5CAug 11, 2026
5NVNemotron 3 Ultra (550B A55B)NVIDIA22.6%0.0%5CAug 11, 2026

TAU3-Bench Score Distribution

A closer view of the leading scores on this benchmark.

TAU3-Bench

TAU3-Bench Highlights

The leading models and scores on this benchmark.

Rank #1MiMo-V2.5-Pro72.9%Rank #2Qwen3.6 Plus70.7%Rank #3GLM-5.170.6%Rank #4Qwen3.6-35B-A3B67.2%

What is TAU3-Bench?

What TAU3-Bench measures and how its scores work.

TAU3-Bench is a benchmark for evaluating general-purpose agent capabilities, testing models on multi-turn interactions with simulated user models, retrieval, and complex decision-making scenarios.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
TAU3-Bench
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
tau3-bench|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about TAU3-Bench.

Which model scores highest on TAU3-Bench?

MiMo-V2.5-Pro is currently ranked first with 72.9%.

What does TAU3-Bench measure?

TAU3-Bench is a benchmark for evaluating general-purpose agent capabilities, testing models on multi-turn interactions with simulated user models, retrieval, and complex decision-making scenarios.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

5 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.

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