TAU2-Bench
TAU2-Bench - agentic tool use benchmark for customer service scenarios. Airline domain evaluated with fixes from Claude Opus 4.5 system card.
Category
General Agents
Score type
percent
Scale
relative
higher is better
Models tested
19
What is TAU2-Bench?
TAU2-Bench is a benchmark for how well a model acts as a general-purpose agent. The official description says: "TAU2-Bench - agentic tool use benchmark for customer service scenarios". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
TAU2-Bench measures how well a model acts as a general-purpose agent. In detail, it checks:
- solving long, multi-step tasks with many intermediate decisions
- using tools correctly (browsers, terminals, APIs, calendars, other apps)
- adapting when something unexpected happens mid-task
- staying on goal over long task horizons instead of wandering off
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: TAU2-Bench - agentic tool use benchmark for customer service scenarios. Airline domain evaluated with fixes from Claude Opus 4.5 system card.
Frequently asked questions
What is the TAU2-Bench benchmark?
TAU2-Bench is a benchmark for how well a model acts as a general-purpose agent. The official description says: 'TAU2-Bench - agentic tool use benchmark for customer service scenarios'. Below we describe in simple words what benchmarks of this type generally examine.
What does TAU2-Bench test?
TAU2-Bench mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: solving long, multi-step tasks with many intermediate decisions; using tools correctly (browsers, terminals, APIs, calendars, other apps); adapting when something unexpected happens mid-task.
How is the TAU2-Bench score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Where do I get TAU2-Bench data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/tau2-bench/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Benchmark dataset
The question/task data itself — download and evaluate locally
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 19 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
MiniCPM5-2B
OpenBMB
|
97.1%
|
— | Report | Verified |
| 2 |
LFM2.5-2.6B
LiquidAI
|
90.4%
|
— | Report | Verified |
| 3 |
Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
|
81.2%
|
01.02.2026 | Report | Unverified |
| 4 |
Qwen3.5-4B
Qwen
|
79.9%
|
01.02.2026 | Report | Verified |
| 5 |
Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
|
79.5%
|
01.02.2026 | Report | Verified |
| 6 |
Qwen3.5-27B
Qwen Team (Alibaba Cloud)
|
79%
|
01.02.2026 | Report | Unverified |
| 7 |
Gemma4-31B-it
Google
|
76.9%
|
02.07.2026 | Report | Verified |
| 8 |
Spark-X2.5-4B
SparkLLM (XHToken)
|
75.1%
|
— | Report | Verified |
| 9 |
Gemma4-12B
Google
|
69%
|
02.07.2026 | Report | Verified |
| 10 |
Gemma4-26B-A4B
Google
|
68.2%
|
02.07.2026 | Report | Verified |
| 11 |
Spark-X2.5-1.7B
SparkLLM (XHToken)
|
65.3%
|
— | Report | Verified |
| 12 |
Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
|
58.5%
|
01.02.2026 | Report | Unverified |
| 13 |
Qwen3.5-2B
Qwen Team (Alibaba Cloud)
|
48.8%
|
— | Report | Verified |
| 14 |
Gemma4-E4B
Google
|
42.2%
|
02.07.2026 | Report | Verified |
| 15 |
granite-4.2-3B
IBM
|
40.9%
|
— | Report | Verified |
| 16 |
Nemotron-3-Nano-4B
NVIDIA
|
28.1%
|
— | Report | Verified |
| 17 |
Gemma4-E2B
Google
|
24.5%
|
02.07.2026 | Report | Verified |
| 18 |
Gemma3-27B
Google
|
16.2%
|
02.07.2026 | Report | Unverified |
| 19 |
LFM2.5-8B-A1B
LiquidAI
|
16.1%
|
— | Report | Verified |