llmboard.aiAI model intelligence
Home

Model Rankings

OverallOpen ModelsAgentCodingReasoningMathKnowledgeInstruction FollowingTextVision
Image GenerationImage Editing
Video GenerationImage to VideoVideo Editing
Text to SpeechSpeech to Text
Embeddings

Efficiency

Chat Token PricingImage PricingVideo PricingAudio Pricing
Chat Speed & LatencyProvider Reliability

Benchmarks

GPQAMMLU-ProAIME 2025SWE-Bench VerifiedMMLUHumanity's Last ExamLiveCodeBenchMATHHumanEvalMMMU-Pro
All Benchmarks

Tools

Model Directory

Scoring & Data

Scoring & Data
1367 models808 benchmarks

Leaderboard Center

Overall RankingCodingCore BenchmarksPrice & ValueRuntime Performance

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Data & Methods

Scoring MethodAll Benchmarks
llmboard.aiCopyright 2026 llmboard.ai

reasoning benchmark

Tau2 Retail Leaderboard

Tau2 Retail evaluates conversational AI agents in retail customer service scenarios within a dual-control environment where both the agent and user can interact with tools.

Updated Oct 23, 2026

Models28
Model coverage28
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
  • Distribution
  • Top models
  • About
  • FAQ

Tau2 Retail Ranking

Higher score ranks better on this benchmark.

28 rows
Columns

Show columns

Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelANClaude Opus 4.6AnthropicScore91.90%Percentile100.00%Participants28EvidenceCEvaluatedOct 22, 2026
Rank02ModelANClaude Sonnet 4.6AnthropicScore91.70%Percentile96.30%Participants28EvidenceCEvaluatedOct 22, 2026
Rank03ModelANClaude Opus 4.5AnthropicScore88.90%Percentile92.59%Participants28EvidenceCEvaluatedOct 22, 2026
Rank04ModelMELongCat-Flash-Thinking-2601MeituanScore88.60%Percentile88.89%Participants28EvidenceCEvaluatedOct 22, 2026
Rank05ModelMEMuse Glimmer-30BMetaScore87.10%Percentile85.19%Participants28EvidenceCEvaluatedOct 22, 2026
Rank06ModelANClaude Haiku 4.5AnthropicScore83.20%Percentile81.48%Participants28EvidenceCEvaluatedOct 22, 2026
Rank07ModelOPGPT-5.2OpenAIScore82.00%Percentile77.78%Participants28EvidenceCEvaluatedOct 22, 2026
Rank08ModelOPGPT-5OpenAIScore81.10%Percentile74.07%Participants28EvidenceCEvaluatedOct 22, 2026
Rank09ModelOPo3OpenAIScore80.20%Percentile70.37%Participants28EvidenceCEvaluatedOct 22, 2026
Rank10ModelAMNova 2 OmniAmazonScore78.30%Percentile66.67%Participants28EvidenceCEvaluatedOct 22, 2026
Rank11ModelLAEXAONE 4.5 33BLG AI ResearchScore77.90%Percentile62.96%Participants28EvidenceCEvaluatedOct 22, 2026
Rank12ModelOPGPT-5.1OpenAIScore77.90%Percentile59.26%Participants28EvidenceCEvaluatedOct 22, 2026
Rank13ModelOPGPT-5.1 InstantOpenAIScore77.90%Percentile55.56%Participants28EvidenceCEvaluatedOct 22, 2026
Rank14ModelOPGPT-5.1 ThinkingOpenAIScore77.90%Percentile51.85%Participants28EvidenceCEvaluatedOct 22, 2026
Rank15ModelAMNova 2 ProAmazonScore77.70%Percentile48.15%Participants28EvidenceCEvaluatedOct 22, 2026
Rank16ModelAMNova 2 LiteAmazonScore76.50%Percentile44.44%Participants28EvidenceCEvaluatedOct 22, 2026
Rank17ModelMELongCat-Flash-LiteMeituanScore73.10%Percentile40.74%Participants28EvidenceCEvaluatedOct 22, 2026
Rank18ModelACQwen3-235B-A22B-Thinking-2507Alibaba Cloud / Qwen TeamScore71.90%Percentile37.04%Participants28EvidenceCEvaluatedOct 22, 2026
Rank19ModelMELongCat-Flash-ThinkingMeituanScore71.50%Percentile33.33%Participants28EvidenceCEvaluatedOct 22, 2026
Rank20ModelACQwen3-235B-A22B-Instruct-2507Alibaba Cloud / Qwen TeamScore71.30%Percentile29.63%Participants28EvidenceCEvaluatedOct 22, 2026
Rank21ModelMELongCat-Flash-ChatMeituanScore71.27%Percentile25.93%Participants28EvidenceCEvaluatedOct 22, 2026
Rank22ModelMAKimi K2 InstructMoonshot AIScore70.60%Percentile22.22%Participants28EvidenceCEvaluatedOct 22, 2026
Rank23ModelMAKimi K2-Instruct-0905Moonshot AIScore70.60%Percentile18.52%Participants28EvidenceCEvaluatedOct 22, 2026
Rank24ModelACQwen3-Next-80B-A3B-ThinkingAlibaba Cloud / Qwen TeamScore67.80%Percentile14.81%Participants28EvidenceCEvaluatedOct 22, 2026
Rank25ModelOPGPT-4oOpenAIScore63.40%Percentile11.11%Participants28EvidenceCEvaluatedOct 22, 2026
Rank26ModelNVNemotron 3 Super (120B A12B)NVIDIAScore62.83%Percentile7.41%Participants28EvidenceCEvaluatedOct 22, 2026
Rank27ModelACQwen3-Next-80B-A3B-InstructAlibaba Cloud / Qwen TeamScore57.30%Percentile3.70%Participants28EvidenceCEvaluatedOct 22, 2026
Rank28ModelNVNemotron 3 Nano (30B A3B)NVIDIAScore56.90%Percentile0.00%Participants28EvidenceCEvaluatedOct 22, 2026

Tau2 Retail Highlights

The leading models and scores on this benchmark.

Tau2 Retail Score Distribution

A closer view of the leading scores on this benchmark.

Tau2 Retail

The Top AI Models for Tau2 Retail

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

What is Tau2 Retail?

What Tau2 Retail measures and how its scores work.

Tau2 Retail is a benchmark for conversational AI agents in retail customer support contexts.

It measures tool-agent-user interaction, rule adherence, and task consistency, reported as a Score ratio.

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

Family
Tau2 Retail
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
overall

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

FAQ

Common questions about Tau2 Retail.

Which model scores highest on Tau2 Retail?

Claude Opus 4.6 is currently ranked first with 91.90%.

What are the top three models on Tau2 Retail?

The current leaders are Claude Opus 4.6 (91.90%), Claude Sonnet 4.6 (91.70%), and Claude Opus 4.5 (88.90%).

Which Tau2 Retail model has the lowest official input price?

Qwen3-Next-80B-A3B-Thinking has the lowest matched official input price at $0.50 input / $6.0 output per 1M tokens.

Which models are fastest among Tau2 Retail results?

The fastest matched records are GPT-4o (132.00 tok/s via OpenAI), Claude Haiku 4.5 (100.00 tok/s via Vertex AI), and GPT-5.2 (100.00 tok/s via OpenAI).

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does Tau2 Retail measure?

It measures tool-agent-user interaction, rule adherence, and task consistency, reported as a Score ratio.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

28 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.

Rank #1Claude Opus 4.691.90%
Rank #2Claude Sonnet 4.691.70%
Rank #3Claude Opus 4.588.90%
Rank #4LongCat-Flash-Thinking-260188.60%

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

  1. 01
    AN
    Claude Opus 4.6Anthropic
    Score
    91.90%
    Price
    $5.0 input / $25 output per 1M tokens
    Speed
    Up to 42.00 tok/s via Anthropic

    Strengths

    • Ranks #1 of 28 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Retail, not total model capability
  2. 02
    AN
    Claude Sonnet 4.6Anthropic
    Score
    91.70%
    Price
    $3.0 input / $15 output per 1M tokens
    Speed
    Up to 42.00 tok/s via Anthropic

    Strengths

    • Ranks #2 of 28 compared models
    • 96th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Retail, not total model capability
  3. 03
    AN
    Anthropic
    Score
    88.90%
    Price
    $5.0 input / $25 output per 1M tokens
    Speed
    Up to 42.00 tok/s via Anthropic

    Strengths

    • Ranks #3 of 28 compared models
    • 93th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Retail, not total model capability
  4. 04
    ME
    Meituan
    Score
    88.60%

    Strengths

    • Ranks #4 of 28 compared models
    • 89th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Retail, not total model capability
  5. 05
    ME
    Meta
    Score
    87.10%

    Strengths

    • Ranks #5 of 28 compared models
    • 85th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures Tau2 Retail, not total model capability

Selection summary

Best AI Models for Tau2 Retail

Claude Opus 4.6 currently leads Tau2 Retail with 91.90%. 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.

Claude Opus 4.5
LongCat-Flash-Thinking-2601
Muse Glimmer-30B
Benchmark rank #1Claude Opus 4.691.90% · $5.0 input / $25 output per 1M tokens
Benchmark rank #2Claude Sonnet 4.691.70% · $3.0 input / $15 output per 1M tokens
Benchmark rank #3Claude Opus 4.588.90% · $5.0 input / $25 output per 1M tokens