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reasoning benchmark

Tau2 Telecom Leaderboard

τ²-Bench telecom domain evaluates conversational agents in a dual-control environment modeled as a Dec-POMDP, where both agent and user use tools in shared telecommunications troubleshooting scenarios that test coordination and communication capabilities.

Updated Aug 17, 2026

Models35
Model coverage35
MetricScore
EvidenceB

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Tau2 Telecom Ranking

Higher score ranks better on this benchmark.

30 of 35 rows
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Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelANClaude Opus 4.6AnthropicScore99.3%Percentile100.0%Participants35EvidenceCEvaluatedAug 17, 2026
Rank02ModelMELongCat-Flash-Thinking-2601MeituanScore99.3%Percentile97.1%Participants35EvidenceCEvaluatedAug 17, 2026
Rank03ModelOPGPT-5.4OpenAIScore98.9%Percentile94.1%Participants35EvidenceCEvaluatedAug 17, 2026
Rank04ModelOPGPT-5.2OpenAIScore98.7%Percentile91.2%Participants35EvidenceCEvaluatedAug 17, 2026
Rank05ModelANClaude Opus 4.5AnthropicScore98.2%Percentile88.2%Participants35EvidenceCEvaluatedAug 17, 2026
Rank06ModelOPGPT-5.5OpenAIScore98.0%Percentile85.3%Participants35EvidenceCEvaluatedAug 17, 2026
Rank07ModelANClaude Sonnet 4.6AnthropicScore97.9%Percentile82.3%Participants35EvidenceCEvaluatedAug 17, 2026
Rank08ModelXIMiMo-V2-ProXiaomiScore96.8%Percentile79.4%Participants35EvidenceCEvaluatedAug 17, 2026
Rank09ModelOPGPT-5OpenAIScore96.7%Percentile76.5%Participants35EvidenceCEvaluatedAug 17, 2026
Rank10ModelOPGPT-5.1OpenAIScore95.6%Percentile73.5%Participants35EvidenceCEvaluatedAug 17, 2026
Rank11ModelOPGPT-5.1 InstantOpenAIScore95.6%Percentile70.6%Participants35EvidenceCEvaluatedAug 17, 2026
Rank12ModelOPGPT-5.1 ThinkingOpenAIScore95.6%Percentile67.7%Participants35EvidenceCEvaluatedAug 17, 2026
Rank13ModelOPGPT-5.4 miniOpenAIScore93.4%Percentile64.7%Participants35EvidenceCEvaluatedAug 17, 2026
Rank14ModelAMNova 2 ProAmazonScore92.7%Percentile61.8%Participants35EvidenceCEvaluatedAug 17, 2026
Rank15ModelOPGPT-5.4 nanoOpenAIScore92.5%Percentile58.8%Participants35EvidenceCEvaluatedAug 17, 2026
Rank16ModelMEMuse SparkMetaScore91.5%Percentile55.9%Participants35EvidenceCEvaluatedAug 17, 2026
Rank17ModelMIMiniMax M2MiniMaxScore87.0%Percentile52.9%Participants35EvidenceCEvaluatedAug 17, 2026
Rank18ModelMIMiniMax M2.1MiniMaxScore87.0%Percentile50.0%Participants35EvidenceCEvaluatedAug 17, 2026
Rank19ModelCOCommand A+CohereScore85.0%Percentile47.1%Participants35EvidenceCEvaluatedAug 17, 2026
Rank20ModelMELongCat-Flash-ThinkingMeituanScore83.1%Percentile44.1%Participants35EvidenceCEvaluatedAug 17, 2026
Rank21ModelANClaude Haiku 4.5AnthropicScore83.0%Percentile41.2%Participants35EvidenceCEvaluatedAug 17, 2026
Rank22ModelAMNova 2 OmniAmazonScore80.0%Percentile38.2%Participants35EvidenceCEvaluatedAug 17, 2026
Rank23ModelAMNova 2 LiteAmazonScore76.0%Percentile35.3%Participants35EvidenceCEvaluatedAug 17, 2026
Rank24ModelMELongCat-Flash-ChatMeituanScore73.7%Percentile32.4%Participants35EvidenceCEvaluatedAug 17, 2026
Rank25ModelMELongCat-Flash-LiteMeituanScore72.8%Percentile29.4%Participants35EvidenceCEvaluatedAug 17, 2026
Rank26ModelMIMAI-Code-1-FlashMicrosoftScore71.7%Percentile26.5%Participants35EvidenceCEvaluatedAug 17, 2026
Rank27ModelMAKimi K2 InstructMoonshot AIScore65.8%Percentile23.5%Participants35EvidenceCEvaluatedAug 17, 2026
Rank28ModelMAKimi K2-Instruct-0905Moonshot AIScore65.8%Percentile20.6%Participants35EvidenceCEvaluatedAug 17, 2026
Rank29ModelNVNemotron 3 Super (120B A12B)NVIDIAScore64.4%Percentile17.6%Participants35EvidenceCEvaluatedAug 17, 2026
Rank30ModelOPo3OpenAIScore58.2%Percentile14.7%Participants35EvidenceCEvaluatedAug 17, 2026
Rank31ModelACQwen3-235B-A22B-Thinking-2507Alibaba Cloud / Qwen TeamScore45.6%Percentile11.8%Participants35EvidenceCEvaluatedAug 17, 2026
Rank32ModelACQwen3-Next-80B-A3B-ThinkingAlibaba Cloud / Qwen TeamScore43.9%Percentile8.8%Participants35EvidenceCEvaluatedAug 17, 2026
Rank33ModelNVNemotron 3 Nano (30B A3B)NVIDIAScore42.2%Percentile5.9%Participants35EvidenceCEvaluatedAug 17, 2026
Rank34ModelOPGPT-4oOpenAIScore23.5%Percentile2.9%Participants35EvidenceCEvaluatedAug 17, 2026
Rank35ModelACQwen3-Next-80B-A3B-InstructAlibaba Cloud / Qwen TeamScore13.2%Percentile0.0%Participants35EvidenceCEvaluatedAug 17, 2026

Tau2 Telecom Highlights

The leading models and scores on this benchmark.

Rank #1Claude Opus 4.699.3%Rank #2LongCat-Flash-Thinking-260199.3%Rank #3GPT-5.498.9%Rank #4GPT-5.298.7%

Tau2 Telecom Score Distribution

A closer view of the leading scores on this benchmark.

Tau2 Telecom

The Top AI Models for Tau2 Telecom

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

Ranking basisThis tau2 telecom AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    AN
    Claude Opus 4.6Anthropic
    Score
    99.3%
    Price
    $5.0 input / $25 output per 1M tokens
    Speed
    Up to 17 tok/s via Anthropic

    Strengths

    • Ranks #1 of 35 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Telecom, not total model capability
  2. 02
    ME
    LongCat-Flash-Thinking-2601Meituan
    Score
    99.3%
    Speed
    Up to 100 tok/s via Meituan

    Strengths

    • Ranks #2 of 35 compared models
    • 97th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Telecom, not total model capability
  3. 03
    OP
    GPT-5.4OpenAI
    Score
    98.9%
    Price
    $2.5 input / $15 output per 1M tokens
    Speed
    Up to 9.1 tok/s via OpenAI

    Strengths

    • Ranks #3 of 35 compared models
    • 94th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Telecom, not total model capability
  4. 04
    OP
    GPT-5.2OpenAI
    Score
    98.7%
    Price
    $1.8 input / $14 output per 1M tokens
    Speed
    Up to 100 tok/s via OpenAI

    Strengths

    • Ranks #4 of 35 compared models
    • 91th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Telecom, not total model capability
  5. 05
    AN
    Claude Opus 4.5Anthropic
    Score
    98.2%
    Price
    $5.0 input / $25 output per 1M tokens
    Speed
    Up to 42 tok/s via Anthropic

    Strengths

    • Ranks #5 of 35 compared models
    • 88th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Telecom, not total model capability

Selection summary

Best AI Models for Tau2 Telecom

Claude Opus 4.6 currently leads Tau2 Telecom with 99.3%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.

Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.

Benchmark rank #1Claude Opus 4.699.3% · $5.0 input / $25 output per 1M tokensBenchmark rank #2LongCat-Flash-Thinking-260199.3% · Up to 100 tok/s via MeituanBenchmark rank #3GPT-5.498.9% · $2.5 input / $15 output per 1M tokens

What is Tau2 Telecom?

What Tau2 Telecom measures and how its scores work.

τ²-Bench telecom domain evaluates conversational agents in a dual-control environment modeled as a Dec-POMDP, where both agent and user use tools in shared telecommunications troubleshooting scenarios that test coordination and communication capabilities.

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

Family
Tau2 Telecom
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
tau2-telecom|llm-stats-current

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

FAQ

Common questions about Tau2 Telecom.

Which model scores highest on Tau2 Telecom?

Claude Opus 4.6 is currently ranked first with 99.3%.

What does Tau2 Telecom measure?

τ²-Bench telecom domain evaluates conversational agents in a dual-control environment modeled as a Dec-POMDP, where both agent and user use tools in shared telecommunications troubleshooting scenarios that test coordination and communication capabilities.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

35 model results are currently shown.

Does this benchmark affect the overall score?

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