tau2-bench
Dual-control customer-service simulations (retail, airline, telecom) where agent and simulated user both act. Graded on final state.
τ³-bench (v1.0.0, 2026-03) lives in the tau2-bench repo and adds banking_knowledge and voice modes. V1.0.1 fixed banking grading. Telecom scores depend on the user-simulator model.
- Made by
- Sierra Research
- Released
- June 2025
- Kind
- Customer service
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
- GPT-5.5 #20 on the capability index
- Last in a launch post
- October 2026
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
GPT-5.4 leads with 98.9%
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.
Gemini 3 Pro leads with 85.4% across all independent runs
Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
GPT-5.4 leads with 98.9%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
- 98.9 GPT-5.4
- 98.0 GPT-5.5
- 97.8
MiniMax-M2.5
- 96.8 MiMo-V2-Pro
- 95.6 Claude Opus 4.6
- 95.3
Ring-2.6-1T
- 94.8 Claude Sonnet 4.6
- 93.6 Claude Opus 4.5
- 93.4 GPT-5.4 Mini
- 92.7
Nova 2.0 Pro Preview
- 92.5 GPT-5.4 Nano
- 92.3
Seed2.0 Pro
- 91.5
Muse Spark
- 91.3
Trinity Large Thinking
- 90.3 GPT-5.2
- 90.2
Gemini 3 Flash
- 89.7 GLM-5
- 88.2
LongCat-Flash-Thinking-2601
- 88.2
Step 3.5 Flash
- 87.4 GLM-4.7
- 87.0
MiniMax-M2
- 87.0
MiniMax-M2.1
- 86.9
Spark-X2.6-4B
- 86.7
Qwen3.5 397B-A17B
- 85.4
Gemini 3 Pro
- 85.0
Command A+
- 84.7 Claude Sonnet 4.5
- 82.6
Keye-VL-2.0-30B-A3B
- 82.1
Qwen3-Max
- 81.2
Qwen3.5-35B-A3B
- 81.0
Qwen3.5-Omni-Plus
- 80.9
Intern-S1-Pro
- 80.3
DeepSeek-V3.2
- 80.3 MiMo-V2-Flash
- 80.2 GPT-5.1
- 80.1 GPT-5
- 80.0
Nova 2 Omni Preview
- 79.9
Qwen3.5-4B
- 79.5 glm-4.7-flash
- 79.5
Qwen3.5-122B-A10B
- 79.1
Qwen3.5-9B
- 79.0
Qwen3.5-27B
- 78.8
ERNIE 5.0
- 78.4
Ring-2.5-1T
- 78.4
Ling-2.6-1T
- 76.9
Gemma 4 31B IT
- 76.6 Claude Haiku 4.5
- 76.0
Nova 2 Lite
- 75.9 GLM-4.6
- 74.0
LongCat-Flash-Thinking
- 73.2
K-EXAONE
- 73.0
Nemotron 3.5 Super VL
- 72.4
Tencent HY 2.0 Think
- 72.3
Solar Pro 3 (March 2026 update)
- 72.0
Seed1.8
- 72.0
EXAONE 4.5 33B
- 71.7
MAI-Code-1-Flash
- 70.8 GPT-5 mini
- 69.0
Gemma 4 12B
- 68.3 Sarvam 105B
- 68.2
Gemma 4 26B A4B
- 67.7
LongCat-Flash-Chat
- 66.1 Kimi K2
- 64.0 LFM2.5-8B-A1B
- 61.1
Nemotron 3 Super
- 58.9
Nemotron-Cascade 2 30B-A3B
- 58.5
Qwen3-235B-A22B-Thinking
- 57.4
Qwen3-Next-80B-A3B
- 56.2
DiffusionGemma 26B A4B
- 55.8
Solar Open 100B
- 52.3
Nemotron 3.5 Bolt E4B
- 49.0
Nemotron 3 Nano 30B-A3B
- 48.8
Qwen3.5-2B
- 46.3 GPT-5 nano
- 45.7 Sarvam 30B
- 42.2
Gemma 4 E4B
- 35.4
Nemotron 3 Nano 4B
- 24.5
Gemma 4 E2B
- 11.6
Qwen3.5-0.8B
- 1 GPT-5.4 98.9%
- 2 GPT-5.5 98%
- 3
MiniMax-M2.5 97.8%
- 4 MiMo-V2-Pro 96.8%
- 5 Claude Opus 4.6 95.6%
- 6
Ring-2.6-1T 95.3%
- 7 Claude Sonnet 4.6 94.8%
- 8 Claude Opus 4.5 93.6%
- 9 GPT-5.4 Mini 93.4%
- 10
Nova 2.0 Pro Preview 92.7%
- 11 GPT-5.4 Nano 92.5%
- 12
Seed2.0 Pro 92.3%
- 13
Muse Spark 91.5%
- 14
Trinity Large Thinking 91.3%
- 15 GPT-5.2 90.3%
- 16
Gemini 3 Flash 90.2%
- 17 GLM-5 89.7%
- 18
LongCat-Flash-Thinking-2601 88.2%
- 19
Step 3.5 Flash 88.2%
- 20 GLM-4.7 87.4%
- 21
MiniMax-M2 87%
- 22
MiniMax-M2.1 87%
- 23
Spark-X2.6-4B 86.9%
- 24
Qwen3.5 397B-A17B 86.7%
- 25
Gemini 3 Pro 85.4%
- 26
Command A+ 85%
- 27 Claude Sonnet 4.5 84.7%
- 28
Keye-VL-2.0-30B-A3B 82.6%
- 29
Qwen3-Max 82.1%
- 30
Qwen3.5-35B-A3B 81.2%
- 31
Qwen3.5-Omni-Plus 81%
- 32
Intern-S1-Pro 80.9%
- 33
DeepSeek-V3.2 80.3%
- 34 MiMo-V2-Flash 80.3%
- 35 GPT-5.1 80.2%
- 36 GPT-5 80.1%
- 37
Nova 2 Omni Preview 80%
- 38
Qwen3.5-4B 79.9%
- 39 glm-4.7-flash 79.5%
- 40
Qwen3.5-122B-A10B 79.5%
- 41
Qwen3.5-9B 79.1%
- 42
Qwen3.5-27B 79%
- 43
ERNIE 5.0 78.8%
- 44
Ring-2.5-1T 78.4%
- 45
Ling-2.6-1T 78.4%
- 46
Gemma 4 31B IT 76.9%
- 47 Claude Haiku 4.5 76.6%
- 48
Nova 2 Lite 76%
- 49 GLM-4.6 75.9%
- 50
LongCat-Flash-Thinking 74%
- 51
K-EXAONE 73.2%
- 52
Nemotron 3.5 Super VL 73%
- 53
Tencent HY 2.0 Think 72.4%
- 54
Solar Pro 3 (March 2026 update) 72.3%
- 55
Seed1.8 72%
- 56
EXAONE 4.5 33B 72%
- 57
MAI-Code-1-Flash 71.7%
- 58 GPT-5 mini 70.8%
- 59
Gemma 4 12B 69%
- 60 Sarvam 105B 68.3%
- 61
Gemma 4 26B A4B 68.2%
- 62
LongCat-Flash-Chat 67.7%
- 63 Kimi K2 Jul 2025 66.1%
- 64 LFM2.5-8B-A1B 64%
- 65
Nemotron 3 Super 61.1%
- 66
Nemotron-Cascade 2 30B-A3B 58.9%
- 67
Qwen3-235B-A22B-Thinking Jul 2025 58.5%
- 68
Qwen3-Next-80B-A3B 57.4%
- 69
DiffusionGemma 26B A4B 56.2%
- 70
Solar Open 100B 55.8%
- 71
Nemotron 3.5 Bolt E4B 52.3%
- 72
Nemotron 3 Nano 30B-A3B 49%
- 73
Qwen3.5-2B 48.8%
- 74 GPT-5 nano 46.3%
- 75 Sarvam 30B 45.7%
- 76
Gemma 4 E4B 42.2%
- 77
Nemotron 3 Nano 4B 35.4%
- 78
Gemma 4 E2B 24.5%
- 79
Qwen3.5-0.8B 11.6%
Source: Labs’ model cards
- 1
Gemini 3 Pro 85.4%
- 2 Claude Sonnet 4.5 84.7%
- 3
Qwen3-Max 82.2%
- 4
DeepSeek-V3.2 80.4%
- 5 GPT-5 80%
- 6 Kimi K2 Jul 2025 64.3%
- 7 Claude 3.7 Sonnet 61.8%
- 8 o4-mini 56.9%
- 9 GPT-4.1 54.7%
- 10 GPT-4.1 mini 53%
Source: Official tau2-bench leaderboard
- 98.9 GPT-5.4
- 98.0 GPT-5.5
- 97.8
MiniMax-M2.5
- 96.8 MiMo-V2-Pro
- 95.6 Claude Opus 4.6
- 95.3
Ring-2.6-1T
- 94.8 Claude Sonnet 4.6
- 93.6 Claude Opus 4.5
- 93.4 GPT-5.4 Mini
- 92.7
Nova 2.0 Pro Preview
- 92.5 GPT-5.4 Nano
- 92.3
Seed2.0 Pro
- 91.5
Muse Spark
- 91.3
Trinity Large Thinking
- 90.3 GPT-5.2
- 90.2
Gemini 3 Flash
- 89.7 GLM-5
- 88.2
LongCat-Flash-Thinking-2601
- 88.2
Step 3.5 Flash
- 87.4 GLM-4.7
- 87.0
MiniMax-M2
- 87.0
MiniMax-M2.1
- 86.9
Spark-X2.6-4B
- 86.7
Qwen3.5 397B-A17B
- 85.4
Gemini 3 Pro
- 85.0
Command A+
- 84.7 Claude Sonnet 4.5
- 82.6
Keye-VL-2.0-30B-A3B
- 82.2
Qwen3-Max
- 81.2
Qwen3.5-35B-A3B
- 81.0
Qwen3.5-Omni-Plus
- 80.9
Intern-S1-Pro
- 80.4
DeepSeek-V3.2
- 80.3 MiMo-V2-Flash
- 80.2 GPT-5.1
- 80.1 GPT-5
- 80.0
Nova 2 Omni Preview
- 79.9
Qwen3.5-4B
- 79.5 glm-4.7-flash
- 79.5
Qwen3.5-122B-A10B
- 79.1
Qwen3.5-9B
- 79.0
Qwen3.5-27B
- 78.8
ERNIE 5.0
- 78.4
Ring-2.5-1T
- 78.4
Ling-2.6-1T
- 76.9
Gemma 4 31B IT
- 76.6 Claude Haiku 4.5
- 76.0
Nova 2 Lite
- 75.9 GLM-4.6
- 74.0
LongCat-Flash-Thinking
- 73.2
K-EXAONE
- 73.0
Nemotron 3.5 Super VL
- 72.4
Tencent HY 2.0 Think
- 72.3
Solar Pro 3 (March 2026 update)
- 72.0
Seed1.8
- 72.0
EXAONE 4.5 33B
- 71.7
MAI-Code-1-Flash
- 70.8 GPT-5 mini
- 69.0
Gemma 4 12B
- 68.3 Sarvam 105B
- 68.2
Gemma 4 26B A4B
- 67.7
LongCat-Flash-Chat
- 66.1 Kimi K2
- 64.0 LFM2.5-8B-A1B
- 61.8 Claude 3.7 Sonnet
- 61.1
Nemotron 3 Super
- 58.9
Nemotron-Cascade 2 30B-A3B
- 58.5
Qwen3-235B-A22B-Thinking
- 57.4
Qwen3-Next-80B-A3B
- 56.9 o4-mini
- 56.2
DiffusionGemma 26B A4B
- 55.8
Solar Open 100B
- 54.7 GPT-4.1
- 53.0 GPT-4.1 mini
- 52.3
Nemotron 3.5 Bolt E4B
- 49.0
Nemotron 3 Nano 30B-A3B
- 48.8
Qwen3.5-2B
- 46.3 GPT-5 nano
- 45.7 Sarvam 30B
- 42.2
Gemma 4 E4B
- 35.4
Nemotron 3 Nano 4B
- 24.5
Gemma 4 E2B
- 11.6
Qwen3.5-0.8B
- 1 GPT-5.4 98.9%
- 2 GPT-5.5 98%
- 3
MiniMax-M2.5 97.8%
- 4 MiMo-V2-Pro 96.8%
- 5 Claude Opus 4.6 95.6%
- 6
Ring-2.6-1T 95.3%
- 7 Claude Sonnet 4.6 94.8%
- 8 Claude Opus 4.5 93.6%
- 9 GPT-5.4 Mini 93.4%
- 10
Nova 2.0 Pro Preview 92.7%
- 11 GPT-5.4 Nano 92.5%
- 12
Seed2.0 Pro 92.3%
- 13
Muse Spark 91.5%
- 14
Trinity Large Thinking 91.3%
- 15 GPT-5.2 90.3%
- 16
Gemini 3 Flash 90.2%
- 17 GLM-5 89.7%
- 18
LongCat-Flash-Thinking-2601 88.2%
- 19
Step 3.5 Flash 88.2%
- 20 GLM-4.7 87.4%
- 21
MiniMax-M2 87%
- 22
MiniMax-M2.1 87%
- 23
Spark-X2.6-4B 86.9%
- 24
Qwen3.5 397B-A17B 86.7%
- 25
Gemini 3 Pro 85.4%
- 26
Command A+ 85%
- 27 Claude Sonnet 4.5 84.7%
- 28
Keye-VL-2.0-30B-A3B 82.6%
- 29
Qwen3-Max 82.2%
- 30
Qwen3.5-35B-A3B 81.2%
- 31
Qwen3.5-Omni-Plus 81%
- 32
Intern-S1-Pro 80.9%
- 33
DeepSeek-V3.2 80.4%
- 34 MiMo-V2-Flash 80.3%
- 35 GPT-5.1 80.2%
- 36 GPT-5 80.1%
- 37
Nova 2 Omni Preview 80%
- 38
Qwen3.5-4B 79.9%
- 39 glm-4.7-flash 79.5%
- 40
Qwen3.5-122B-A10B 79.5%
- 41
Qwen3.5-9B 79.1%
- 42
Qwen3.5-27B 79%
- 43
ERNIE 5.0 78.8%
- 44
Ring-2.5-1T 78.4%
- 45
Ling-2.6-1T 78.4%
- 46
Gemma 4 31B IT 76.9%
- 47 Claude Haiku 4.5 76.6%
- 48
Nova 2 Lite 76%
- 49 GLM-4.6 75.9%
- 50
LongCat-Flash-Thinking 74%
- 51
K-EXAONE 73.2%
- 52
Nemotron 3.5 Super VL 73%
- 53
Tencent HY 2.0 Think 72.4%
- 54
Solar Pro 3 (March 2026 update) 72.3%
- 55
Seed1.8 72%
- 56
EXAONE 4.5 33B 72%
- 57
MAI-Code-1-Flash 71.7%
- 58 GPT-5 mini 70.8%
- 59
Gemma 4 12B 69%
- 60 Sarvam 105B 68.3%
- 61
Gemma 4 26B A4B 68.2%
- 62
LongCat-Flash-Chat 67.7%
- 63 Kimi K2 Jul 2025 66.1%
- 64 LFM2.5-8B-A1B 64%
- 65 Claude 3.7 Sonnet 61.8%
- 66
Nemotron 3 Super 61.1%
- 67
Nemotron-Cascade 2 30B-A3B 58.9%
- 68
Qwen3-235B-A22B-Thinking Jul 2025 58.5%
- 69
Qwen3-Next-80B-A3B 57.4%
- 70 o4-mini 56.9%
- 71
DiffusionGemma 26B A4B 56.2%
- 72
Solar Open 100B 55.8%
- 73 GPT-4.1 54.7%
- 74 GPT-4.1 mini 53%
- 75
Nemotron 3.5 Bolt E4B 52.3%
- 76
Nemotron 3 Nano 30B-A3B 49%
- 77
Qwen3.5-2B 48.8%
- 78 GPT-5 nano 46.3%
- 79 Sarvam 30B 45.7%
- 80
Gemma 4 E4B 42.2%
- 81
Nemotron 3 Nano 4B 35.4%
- 82
Gemma 4 E2B 24.5%
- 83
Qwen3.5-0.8B 11.6%
Sources: Labs’ model cards and official tau2-bench leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.4 | 98.9% | Mar 2026 | Lab model card | |
| 2 | GPT-5.5 | 98% | Apr 2026 | Lab model card | |
| 3 | | 97.8% | Feb 2026 | Lab model card | |
| 4 | MiMo-V2-Pro | 96.8% | Mar 2026 | Lab model card | |
| 5 | Claude Opus 4.6 | 95.6% | Feb 2026 | Lab model card | |
| 6 | | 95.3% | May 2026 | Lab model card | |
| 7 | Claude Sonnet 4.6 | 94.8% | Feb 2026 | Lab model card | |
| 8 | Claude Opus 4.5 | 93.6% | Nov 2025 | Lab model card | |
| 9 | GPT-5.4 Mini | 93.4% | Mar 2026 | Lab model card | |
| 10 | | 92.7% | Dec 2025 | Lab model card | |
| 11 | GPT-5.4 Nano | 92.5% | Mar 2026 | Lab model card | |
| 12 | | 92.3% | Feb 2026 | Lab model card | |
| 13 | | 91.5% | Apr 2026 | Lab model card | |
| 14 | | 91.3% | Apr 2026 | Lab model card | |
| 15 | GPT-5.2 | 90.3% | Dec 2025 | Lab model card | |
| 16 | | 90.2% | Dec 2025 | Lab model card | |
| 17 | GLM-5 | 89.7% | Feb 2026 | Lab model card | |
| 18 | | 88.2% | Jan 2026 | Lab model card | |
| 19 | | 88.2% | Feb 2026 | Lab model card | |
| 20 | GLM-4.7 | 87.4% | Dec 2025 | Lab model card | |
| 21 | | 87% | Oct 2025 | Lab model card | |
| 22 | | 87% | Dec 2025 | Lab model card | |
| 23 | | 86.9% | Oct 2026 | Lab model card | |
| 24 | | 86.7% | Feb 2026 | Lab model card | |
| 25 | | 85.4% | Nov 2025 | Lab model card | |
| 26 | | 85% | May 2026 | Lab model card | |
| 27 | Claude Sonnet 4.5 | 84.7% | Sep 2025 | Lab model card | |
| 28 | | 82.6% | May 2026 | Lab model card | |
| 29 | | 82.1% | Jan 2026 | Lab model card | |
| 30 | | 81.2% | Feb 2026 | Lab model card | |
| 31 | | 81% | Mar 2026 | Lab model card | |
| 32 | | 80.9% | Feb 2026 | Lab model card | |
| 33 | | 80.3% | Dec 2025 | Lab model card | |
| 34 | MiMo-V2-Flash | 80.3% | Dec 2025 | Lab model card | |
| 35 | GPT-5.1 | 80.2% | Nov 2025 | Lab model card | |
| 36 | GPT-5 | 80.1% | Aug 2025 | Lab model card | |
| 37 | | 80% | Dec 2025 | Lab model card | |
| 38 | | 79.9% | Mar 2026 | Lab model card | |
| 39 | glm-4.7-flash | 79.5% | Jan 2026 | Lab model card | |
| 40 | | 79.5% | Feb 2026 | Lab model card | |
| 41 | | 79.1% | Mar 2026 | Lab model card | |
| 42 | | 79% | Feb 2026 | Lab model card | |
| 43 | | 78.8% | Feb 2026 | Lab model card | |
| 44 | | 78.4% | Feb 2026 | Lab model card | |
| 45 | | 78.4% | Apr 2026 | Lab model card | |
| 46 | | 76.9% | Apr 2026 | Lab model card | |
| 47 | Claude Haiku 4.5 | 76.6% | Oct 2025 | Lab model card | |
| 48 | | 76% | Dec 2025 | Lab model card | |
| 49 | GLM-4.6 | 75.9% | Sep 2025 | Lab model card | |
| 50 | | 74% | Sep 2025 | Lab model card | |
| 51 | | 73.2% | Jan 2026 | Lab model card | |
| 52 | | 73% | Oct 2026 | Lab model card | |
| 53 | | 72.4% | Dec 2025 | Lab model card | |
| 54 | | 72.3% | Mar 2026 | Lab model card | |
| 55 | | 72% | Dec 2025 | Lab model card | |
| 56 | | 72% | Apr 2026 | Lab model card | |
| 57 | | 71.7% | Jun 2026 | Lab model card | |
| 58 | GPT-5 mini | 70.8% | Aug 2025 | Lab model card | |
| 59 | | 69% | Jun 2026 | Lab model card | |
| 60 | Sarvam 105B | 68.3% | Mar 2026 | Lab model card | |
| 61 | | 68.2% | Apr 2026 | Lab model card | |
| 62 | | 67.7% | Aug 2025 | Lab model card | |
| 63 | Kimi K2 Jul 2025 | 66.1% | Jul 2025 | Lab model card | |
| 64 | LFM2.5-8B-A1B | 64% | May 2026 | Lab model card | |
| 65 | | 61.1% | Mar 2026 | Lab model card | |
| 66 | | 58.9% | Mar 2026 | Lab model card | |
| 67 | | 58.5% | Jul 2025 | Lab model card | |
| 68 | | 57.4% | Sep 2025 | Lab model card | |
| 69 | | 56.2% | Jun 2026 | Lab model card | |
| 70 | | 55.8% | Dec 2025 | Lab model card | |
| 71 | | 52.3% | Oct 2026 | Lab model card | |
| 72 | | 49% | Dec 2025 | Lab model card | |
| 73 | | 48.8% | Mar 2026 | Lab model card | |
| 74 | GPT-5 nano | 46.3% | Aug 2025 | Lab model card | |
| 75 | Sarvam 30B | 45.7% | Mar 2026 | Lab model card | |
| 76 | | 42.2% | Apr 2026 | Lab model card | |
| 77 | | 35.4% | Mar 2026 | Lab model card | |
| 78 | | 24.5% | Apr 2026 | Lab model card | |
| 79 | | 11.6% | Mar 2026 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 85.4% | Nov 2025 | Official leaderboard | |
| 2 | Claude Sonnet 4.5 | 84.7% | Sep 2025 | Official leaderboard | |
| 3 | | 82.2% | Sep 2025 | Official leaderboard | |
| 4 | | 80.4% | Dec 2025 | Official leaderboard | |
| 5 | GPT-5 | 80% | Aug 2025 | Official leaderboard | |
| 6 | Kimi K2 Jul 2025 | 64.3% | Jul 2025 | Official leaderboard | |
| 7 | Claude 3.7 Sonnet | 61.8% | Feb 2025 | Official leaderboard | |
| 8 | o4-mini | 56.9% | Apr 2025 | Official leaderboard | |
| 9 | GPT-4.1 | 54.7% | Apr 2025 | Official leaderboard | |
| 10 | GPT-4.1 mini | 53% | Apr 2025 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.4 | 98.9% | Mar 2026 | Lab model card | |
| 2 | GPT-5.5 | 98% | Apr 2026 | Lab model card | |
| 3 | | 97.8% | Feb 2026 | Lab model card | |
| 4 | MiMo-V2-Pro | 96.8% | Mar 2026 | Lab model card | |
| 5 | Claude Opus 4.6 | 95.6% | Feb 2026 | Lab model card | |
| 6 | | 95.3% | May 2026 | Lab model card | |
| 7 | Claude Sonnet 4.6 | 94.8% | Feb 2026 | Lab model card | |
| 8 | Claude Opus 4.5 | 93.6% | Nov 2025 | Lab model card | |
| 9 | GPT-5.4 Mini | 93.4% | Mar 2026 | Lab model card | |
| 10 | | 92.7% | Dec 2025 | Lab model card | |
| 11 | GPT-5.4 Nano | 92.5% | Mar 2026 | Lab model card | |
| 12 | | 92.3% | Feb 2026 | Lab model card | |
| 13 | | 91.5% | Apr 2026 | Lab model card | |
| 14 | | 91.3% | Apr 2026 | Lab model card | |
| 15 | GPT-5.2 | 90.3% | Dec 2025 | Lab model card | |
| 16 | | 90.2% | Dec 2025 | Lab model card | |
| 17 | GLM-5 | 89.7% | Feb 2026 | Lab model card | |
| 18 | | 88.2% | Jan 2026 | Lab model card | |
| 19 | | 88.2% | Feb 2026 | Lab model card | |
| 20 | GLM-4.7 | 87.4% | Dec 2025 | Lab model card | |
| 21 | | 87% | Oct 2025 | Lab model card | |
| 22 | | 87% | Dec 2025 | Lab model card | |
| 23 | | 86.9% | Oct 2026 | Lab model card | |
| 24 | | 86.7% | Feb 2026 | Lab model card | |
| 25 | | 85.4% | Nov 2025 | Official leaderboard | |
| 26 | | 85% | May 2026 | Lab model card | |
| 27 | Claude Sonnet 4.5 | 84.7% | Sep 2025 | Official leaderboard | |
| 28 | | 82.6% | May 2026 | Lab model card | |
| 29 | | 82.2% | Sep 2025 | Official leaderboard | |
| 30 | | 81.2% | Feb 2026 | Lab model card | |
| 31 | | 81% | Mar 2026 | Lab model card | |
| 32 | | 80.9% | Feb 2026 | Lab model card | |
| 33 | | 80.4% | Dec 2025 | Official leaderboard | |
| 34 | MiMo-V2-Flash | 80.3% | Dec 2025 | Lab model card | |
| 35 | GPT-5.1 | 80.2% | Nov 2025 | Lab model card | |
| 36 | GPT-5 | 80.1% | Aug 2025 | Lab model card | |
| 37 | | 80% | Dec 2025 | Lab model card | |
| 38 | | 79.9% | Mar 2026 | Lab model card | |
| 39 | glm-4.7-flash | 79.5% | Jan 2026 | Lab model card | |
| 40 | | 79.5% | Feb 2026 | Lab model card | |
| 41 | | 79.1% | Mar 2026 | Lab model card | |
| 42 | | 79% | Feb 2026 | Lab model card | |
| 43 | | 78.8% | Feb 2026 | Lab model card | |
| 44 | | 78.4% | Feb 2026 | Lab model card | |
| 45 | | 78.4% | Apr 2026 | Lab model card | |
| 46 | | 76.9% | Apr 2026 | Lab model card | |
| 47 | Claude Haiku 4.5 | 76.6% | Oct 2025 | Lab model card | |
| 48 | | 76% | Dec 2025 | Lab model card | |
| 49 | GLM-4.6 | 75.9% | Sep 2025 | Lab model card | |
| 50 | | 74% | Sep 2025 | Lab model card | |
| 51 | | 73.2% | Jan 2026 | Lab model card | |
| 52 | | 73% | Oct 2026 | Lab model card | |
| 53 | | 72.4% | Dec 2025 | Lab model card | |
| 54 | | 72.3% | Mar 2026 | Lab model card | |
| 55 | | 72% | Dec 2025 | Lab model card | |
| 56 | | 72% | Apr 2026 | Lab model card | |
| 57 | | 71.7% | Jun 2026 | Lab model card | |
| 58 | GPT-5 mini | 70.8% | Aug 2025 | Lab model card | |
| 59 | | 69% | Jun 2026 | Lab model card | |
| 60 | Sarvam 105B | 68.3% | Mar 2026 | Lab model card | |
| 61 | | 68.2% | Apr 2026 | Lab model card | |
| 62 | | 67.7% | Aug 2025 | Lab model card | |
| 63 | Kimi K2 Jul 2025 | 66.1% | Jul 2025 | Lab model card | |
| 64 | LFM2.5-8B-A1B | 64% | May 2026 | Lab model card | |
| 65 | Claude 3.7 Sonnet | 61.8% | Feb 2025 | Official leaderboard | |
| 66 | | 61.1% | Mar 2026 | Lab model card | |
| 67 | | 58.9% | Mar 2026 | Lab model card | |
| 68 | | 58.5% | Jul 2025 | Lab model card | |
| 69 | | 57.4% | Sep 2025 | Lab model card | |
| 70 | o4-mini | 56.9% | Apr 2025 | Official leaderboard | |
| 71 | | 56.2% | Jun 2026 | Lab model card | |
| 72 | | 55.8% | Dec 2025 | Lab model card | |
| 73 | GPT-4.1 | 54.7% | Apr 2025 | Official leaderboard | |
| 74 | GPT-4.1 mini | 53% | Apr 2025 | Official leaderboard | |
| 75 | | 52.3% | Oct 2026 | Lab model card | |
| 76 | | 49% | Dec 2025 | Lab model card | |
| 77 | | 48.8% | Mar 2026 | Lab model card | |
| 78 | GPT-5 nano | 46.3% | Aug 2025 | Lab model card | |
| 79 | Sarvam 30B | 45.7% | Mar 2026 | Lab model card | |
| 80 | | 42.2% | Apr 2026 | Lab model card | |
| 81 | | 35.4% | Mar 2026 | Lab model card | |
| 82 | | 24.5% | Apr 2026 | Lab model card | |
| 83 | | 11.6% | Mar 2026 | Lab model card |
The benchmark's own leaderboard has 10 models. Switch the scores above to rank them together.
8 models have held number one in labs’ own numbers since its release in June 2025 6 models have held number one across all independent runs since its release in June 2025 10 models have held number one with claims included since its release in June 2025
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
Sources: Official tau2-bench leaderboard and labs’ model cards
MiniMax’s own number for MiniMax-M2 passed 85% in October 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official tau2-bench leaderboard and labs’ model cards
4 labs 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 |
|---|---|---|---|
| Oct 23, 2026 | 52.3 | Tau2-Bench | |
| Oct 22, 2026 | 86.9 | τ²-bench | |
| Oct 15, 2026 | 73 | Mean of tau2-bench Retail 69.24 / Airline 76.50 / Telecom 73.19 | |
| Jun 10, 2026 | 56.2 | Tau2 (average over 3) | |
| Jun 3, 2026 | 69 | Tau2 (average over 3) | |
| Jun 2, 2026 | 71.7 | 𝜏²-Bench telecom | |
| May 28, 2026 | LFM2.5-8B-A1B | 64 | Mean of Tau² Telecom 88.07 / Tau² Retail 39.82 |
| May 25, 2026 | 82.6 | TAU2-Bench | |
| May 20, 2026 | 85 | τ²-Bench Telecom only (chart label) | |
| May 14, 2026 | 95.3 | Tau2-Bench Telecom scenario only (high) | |
| Apr 29, 2026 | 78.4 | TAU2-Bench | |
| Apr 23, 2026 | GPT-5.5 | 98 | Tau2-bench Telecom (original prompts) |
| Apr 9, 2026 | 69.1 | Mean of τ2-Bench Retail 77.9 / Airline 56.5 / Telecom 73.0 | |
| Apr 8, 2026 | 91.5 | τ²-Bench Telecom (Agentic Tool Use (Artificial Analysis)) | |
| Apr 2, 2026 | 42.2 | Tau2 (average over 3) | |
| Apr 2, 2026 | 24.5 | Tau2 (average over 3) | |
| Apr 2, 2026 | 68.2 | Tau2 (average over 3) | |
| Apr 2, 2026 | 76.9 | Tau2 (average over 3) | |
| Apr 1, 2026 | 91.3 | Mean of Tau2-Airline 88.0 / Tau2-Telecom 94.7 | |
| Mar 30, 2026 | 81 | TAU2Bench | |
| Mar 24, 2026 | 72.3 | Tau2-all | |
| Mar 19, 2026 | 58.9 | τ²-Bench | |
| Mar 18, 2026 | MiMo-V2-Pro | 96.8 | τ2-bench (Telecom) |
| Mar 17, 2026 | GPT-5.4 Nano | 92.5 | τ2-bench (telecom) |
| Mar 17, 2026 | GPT-5.4 Mini | 93.4 | τ²-bench telecom |
| Mar 16, 2026 | 35.4 | Mean of Tau2 Airline 33.3 / Retail 39.8 / Telecom 33 (reasoning on) | |
| Mar 11, 2026 | 61.1 | TauBench V2 Average of Airline 56.25 / Retail 62.83 / Telecom 64.36 | |
| Mar 6, 2026 | Sarvam 30B | 45.7 | Tau2 (avg.) |
| Mar 6, 2026 | Sarvam 105B | 68.3 | Tau2 (avg.) |
| Mar 5, 2026 | GPT-5.4 | 98.9 | Tau2-bench Telecom (xhigh; body chart shows 64.3% without reasoning) |
| Mar 2, 2026 | 11.6 | TAU2-Bench | |
| Mar 2, 2026 | 48.8 | TAU2-Bench | |
| Mar 2, 2026 | 79.9 | TAU2-Bench | |
| Mar 2, 2026 | 79.1 | TAU2-Bench | |
| Feb 24, 2026 | 81.2 | TAU2-Bench | |
| Feb 24, 2026 | 79 | TAU2-Bench | |
| Feb 24, 2026 | 79.5 | TAU2-Bench (airline fixes from Claude Opus 4.5 system card) | |
| Feb 19, 2026 | Mean of τ2-bench, Retail / τ2-bench, Telecom | ||
| Feb 17, 2026 | Claude Sonnet 4.6 | 94.8 | Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Telecom |
| Feb 16, 2026 | 86.7 | TAU2-Bench | |
| Feb 14, 2026 | 92.3 | Mean of τ2-Bench (retail) 90.4 / τ2-Bench (telecom) 94.2 | |
| Feb 12, 2026 | 97.8 | τ² Telecom | |
| Feb 11, 2026 | GLM-5 | 89.7 | τ²-Bench |
| Feb 10, 2026 | 78.4 | Tau2-Bench (Mean@3) | |
| Feb 6, 2026 | 78.8 | TAU2-Bench | |
| Feb 5, 2026 | Claude Opus 4.6 | 95.6 | Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Telecom |
| Feb 2, 2026 | 80.9 | Tau2-Bench | |
| Feb 2, 2026 | 88.2 | τ²-Bench | |
| Jan 23, 2026 | 82.1 | Tau² Bench | |
| Jan 19, 2026 | glm-4.7-flash | 79.5 | τ²-Bench |
| Jan 14, 2026 | 88.2 | τ²-Avg (Avg@4): Retail 88.6 / Airline 76.5 / Telecom 99.3 | |
| Dec 31, 2025 | 55.8 | Mean of Tau² Airline 52.4 / Telecom 55.6 / Retail 59.3 | |
| Dec 31, 2025 | 70.8 | Mean of τ2-Bench Retail 78.6 / Airline 60.4 / Telecom 73.5 | |
| Dec 23, 2025 | 87 | 𝜏²-Bench Telecom | |
| Dec 22, 2025 | GLM-4.7 | 87.4 | τ²-Bench |
| Dec 18, 2025 | 72 | τ2-Bench | |
| Dec 17, 2025 | 90.2 | τ2-bench | |
| Dec 16, 2025 | MiMo-V2-Flash | 80.3 | τ²-Bench |
| Dec 15, 2025 | 49 | TauBench V2 (Average) of Airline 48.0 / Retail 56.9 / Telecom 42.2 | |
| Dec 11, 2025 | GPT-5.2 | 90.3 | Mean of Tau2-bench Telecom Tool use in customer support / Tau2-bench Retail Tool use in customer support |
| Dec 5, 2025 | 72.4 | Tau2-Bench | |
| Dec 2, 2025 | 80 | τ2-bench Telecom only (as benchmarked by Artificial Analysis) | |
| Dec 2, 2025 | 76 | τ2-bench Telecom only (as benchmarked by Artificial Analysis) | |
| Dec 2, 2025 | 92.7 | τ2-bench Telecom only (as benchmarked by Artificial Analysis) | |
| Dec 1, 2025 | 80.3 | τ2-Bench (Pass@1) | |
| Nov 24, 2025 | Claude Opus 4.5 | 93.6 | Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Telecom |
| Nov 19, 2025 | Grok 4.1 Fast | τ²-bench Telecom (chart) | |
| Nov 18, 2025 | 85.4 | τ2-bench | |
| Nov 13, 2025 | GPT-5.1 | 80.2 | Mean of Tau2-bench Airline / Tau2-bench Telecom* / Tau2-bench Retail |
| Oct 27, 2025 | 87 | Best of τ²-Bench / τ²-Bench-Telecom (AA) | |
| Oct 15, 2025 | Claude Haiku 4.5 | 76.6 | Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Airline / Agentic tool use τ2-bench Telecom |
| Sep 30, 2025 | GLM-4.6 | 75.9 | τ²-Bench (Weighted) |
| Sep 29, 2025 | Claude Sonnet 4.5 | 84.7 | Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Airline / Agentic tool use τ2-bench Telecom |
| Sep 24, 2025 | 74.8 | Tau2-Bench (Weighted) | |
| Sep 21, 2025 | 74 | Mean of τ²-Bench-Retail 71.5 / τ²-Bench-Airline 67.5 / τ²-Bench-Telecom 83.1 (Mean@4) | |
| Sep 11, 2025 | 57.4 | Mean of TAU2-Retail 67.8 / TAU2-Airline 60.5 / TAU2-Telecom 43.9 | |
| Aug 29, 2025 | 67.7 | Mean of τ²-Bench (telecom) 73.68 / (airline) 58.00 / (retail) 71.27 (avg@4) | |
| Aug 7, 2025 | GPT-5 nano | 46.3 | Mean of Tau2-bench airline 41.0 / retail 62.3 / telecom 35.5 |
| Aug 7, 2025 | GPT-5 mini | 70.8 | Mean of Tau2-bench airline 60.0 / retail 78.3 / telecom 74.1 |
| Aug 7, 2025 | GPT-5 | 80.1 | Mean of Tau2-bench Function calling (airline) / Tau2-bench Function calling (retail) / Tau2-bench Function calling (telecom) |
| Jul 25, 2025 | 58.5 | Mean of TAU2-Retail / TAU2-Airline / TAU2-Telecom | |
| Jul 11, 2025 | Kimi K2 | 64.3 | Mean of Tau2 retail, Avg@4 / Tau2 airline, Avg@4 / Tau2 telecom, Avg@4 |
40 system cards report it, from 21 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Oct 23, 2026 | | 52.3 | tau2-Bench, released Q4_K_M imatrix checkpoint (Table 5). BF16 55.1 (Table 3) | Capabilities |
| Oct 19, 2026 | | TauBench, three splits with no overall, high: Airline 78.0, Retail 87.1, Telecom 94.1. The telecom split suggests tau2-bench, though the text cites Yao et al. 2024 (Table 5) | Capabilities | |
| Oct 15, 2026 | | Tau2 Retail 69.24, Airline 76.50, Telecom 73.19, no overall score (Table 10) | Capabilities | |
| Oct 15, 2026 | | Tau2 Telecom only, BF16 acc. 59.65 (Table 22) | Capabilities | |
| Jul 31, 2026 | | Tau2, three domains with no overall score: Retail 71.5, Airline 69.0, Telecom 28.1, TD (Table 3) | Capabilities | |
| Jul 24, 2026 | | Tau2, three domains with no overall score: airline 75.0, retail 86.4, telecom 69.3 (Table 5) | Capabilities | |
| Jul 24, 2026 | | Tau2, three domains with no overall score: airline 76.0, retail 85.5, telecom 43.0 (Table 5) | Capabilities | |
| Jun 13, 2026 | | 83.4 | τ2-Average (Acc), xhigh, Retail 77.85, Airline 77.50, Telecom 94.96 (Table 6). High gives Average 84.26, Telecom 96.71 | Capabilities |
| Jun 13, 2026 | | 78.4 | τ2-bench, Mean@4, user model gpt-5.2, average of Retail, Airline and Telecom (Table 5) | Capabilities |
| Jun 9, 2026 | | 82.6 | τ2-Bench (Table 4) | Capabilities |
| Jun 2, 2026 | | 71.7 | tau2-Bench telecom, agentic tool use (Instruction following table) | Capabilities |
| Apr 27, 2026 | | TauBench V2 (Telecom) only, 42.7, no overall score (Table 10) | Capabilities | |
| Apr 17, 2026 | | 81 | TAU2Bench (Table 4) | Capabilities |
| Apr 9, 2026 | | 72 | tau2-Bench weighted average stated in the 3.3 text. Retail 77.9, Airline 56.5, Telecom 73.0 (Table 3, Reasoning mode) | Capabilities |
| Mar 26, 2026 | | 80.9 | τ2-Bench, official settings, thinking (Table 2) | Capabilities |
| Mar 21, 2026 | | 72 | τ2-Bench (Table 4) | Capabilities |
| Mar 19, 2026 | | 58.9 | τ2-Bench, latest-turn thought retention, which the report says adds 3 to 5 points over the official policy (Table 1 and A.6) | Capabilities |
| Mar 11, 2026 | | 61.1 | TauBench V2 Average of Airline 56.25, Retail 62.83, Telecom 64.36 (Table 5) | Capabilities |
| Feb 19, 2026 | | τ2-bench, Retail 90.8% and Telecom 99.3%, no overall (results table, p.4) | Capabilities | |
| Feb 17, 2026 | GLM-5 technical report | 89.7 | τ2-Bench, prompt-adjusted user simulator (Table 7) | Capabilities |
| Feb 17, 2026 | Claude Sonnet 4.6 system card | τ²-bench, Retail 91.7 and Telecom 97.9, Airline not reported, no overall (Table 2.1.A, 2.5) | Capabilities | |
| Feb 14, 2026 | | τ2-Bench retail 90.4, telecom 94.2, no overall (Table 11) | Capabilities | |
| Feb 11, 2026 | | 88.2 | τ2-Bench, avg of 8 runs, fixed airline tasks (Table 5 and E.2.3) | Capabilities |
| Feb 5, 2026 | Claude Opus 4.6 system card | τ²-bench, Retail 91.9 and Telecom 99.3, Airline not reported, no overall (Table 2.3.A, 2.7) | Capabilities | |
| Feb 4, 2026 | | 78.8 | TAU2-Bench (Table 2) | Capabilities |
| Jan 23, 2026 | | 88.2 | τ2-Avg (Avg@4), GPT-4.1 user simulator, cleaned airline subset, Retail 88.6, Airline 76.5, Telecom 99.3 (Table 2) | Capabilities |
| Jan 11, 2026 | | Tau2 Airline 52.4, Telecom 55.6, Retail 59.3, no overall score (Table 6) | Capabilities | |
| Jan 6, 2026 | MiMo-V2-Flash technical report | 80.3 | τ2-Bench, DeepSeek-V3.2 as user agent (Table 9). Telecom 95.3, Retail 79.5, Airline 66.0 (4.5.2) | Capabilities |
| Jan 5, 2026 | | τ2-Telecom only, 25.4, no overall tau2-bench score (Table 5) | Capabilities | |
| Jan 5, 2026 | | 73.2 | tau2-Bench weighted average stated in the 4.2 text. Retail 78.6, Airline 60.4, Telecom 73.5 (Table 3, Reasoning mode). Non-reasoning 73.2, 42.6, 44.0 (Table 4) | Capabilities |
| Dec 23, 2025 | | 49 | TauBench V2 Average (Table 3). Airline 48.00, Retail 56.91, Telecom 42.21 | Capabilities |
| Dec 2, 2025 | | tau2-bench Telecom only 80.0, numbers as benchmarked by Artificial Analysis (Table 5) | Capabilities | |
| Dec 2, 2025 | | tau2-bench Telecom only 76.0, numbers as benchmarked by Artificial Analysis (Table 2) | Capabilities | |
| Dec 2, 2025 | | tau2-bench Telecom only 92.7, numbers as benchmarked by Artificial Analysis (Table 2) | Capabilities | |
| Dec 1, 2025 | | 80.3 | τ2-Bench (Pass@1), average of categories: Airline 63.8, Retail 81.1, Telecom 96.2, DeepSeek-V3.2 Thinking (Table 2) | Capabilities |
| Nov 26, 2025 | | TAU2-Retail 67.0, TAU2-Airline 62.0, TAU2-Telecom 44.7, no overall (Table 6) | Capabilities | |
| Nov 24, 2025 | Claude Opus 4.5 system card | τ²-Bench, Retail 88.9% and Telecom 98.2% without extended thinking, no overall (Table 2.3.A). Airline 67.9% original and 87.8% corrected per Table 2.3.A footnote 6. Table 2.8.A prints Airline original 70.1% | Capabilities | |
| Sep 23, 2025 | | τ2-Bench-Retail 71.5, Airline 67.5, Telecom 83.1 (Mean@4), no overall score (Table 2) | Capabilities | |
| Sep 1, 2025 | | τ2-Bench telecom 73.68, airline 58.00, retail 71.27 (avg@4), no overall score (Table 3) | Capabilities | |
| Jul 21, 2025 | Kimi K2 technical report | 66.1 | τ2-Bench micro Pass@1 across domains (Appendix C text). Avg@4: retail 70.6, airline 56.5, telecom 65.8 (Table 3) | Capabilities |
6 lab claims next to the leaderboard
Each score a lab reported for its own model, beside the same model's best score on the leaderboard. Gaps mostly come from different harnesses, effort levels and task subsets. 5 of them match, which usually means one side copied the other. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| Kimi K2 Jul 2025 | 66.1% τ2-Bench micro Pass@1 across domains (Appendix C text). Avg@4: retail 70.6, airline 56.5, telecom 65.8 (Table 3) | 64.3% Leaderboard | +1.8 pts |
| GPT-5 | 80.1% Mean of Tau2-bench Function calling (airline) / Tau2-bench Function calling (retail) / Tau2-bench Function calling (telecom) | 80% Leaderboard | Same |
| | 82.1% Tau² Bench | 82.2% Leaderboard | Same |
| | 80.3% τ2-Bench (Pass@1) | 80.4% Leaderboard | Same |
| Claude Sonnet 4.5 | 84.7% Mean of Agentic tool use τ2-bench Retail / Agentic tool use τ2-bench Airline / Agentic tool use τ2-bench Telecom | 84.7% Leaderboard | Same |
| | 85.4% τ2-bench | 85.4% Leaderboard | Same |
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
Sources: Official leaderboards and labs’ model cards
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