TauBench V3 Airline
TauBench V3 - Airline domain. Agentic tool use benchmark for airline customer service.
Category
General Agents
Score type
percent
Scale
100%
higher is better
Models tested
4
What is TauBench V3 Airline?
τ-bench Retail simulates a customer-service agent in a retail business. The model talks to a simulated user and must use the company's tools (orders, refunds, policy rules) to actually solve the customer's problem. Only when the database state ends up exactly right does the task count as solved.
What does it test?
TauBench V3 Airline measures how well a model acts as a general-purpose agent. In detail, it checks:
- calling tools with correct arguments
- following written policies while serving the simulated customer
- multi-turn conversation behaviour (asking, confirming, acting)
- correct final database results, not just polite replies
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.
Frequently asked questions
What is the TauBench V3 Airline benchmark?
τ-bench Retail simulates a customer-service agent in a retail business. The model talks to a simulated user and must use the company's tools (orders, refunds, policy rules) to actually solve the customer's problem. Only when the database state ends up exactly right does the task count as solved.
What does TauBench V3 Airline test?
TauBench V3 Airline mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: calling tools with correct arguments; following written policies while serving the simulated customer; multi-turn conversation behaviour (asking, confirming, acting).
How is the TauBench V3 Airline score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get TauBench V3 Airline 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/taubench-v3-airline/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 4 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Kimi K2.6
Moonshot AI
|
85.8%
|
04.06.2026 | Report | Unverified |
| 2 |
NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
NVIDIA
|
81.5%
|
04.06.2026 | Report | Verified |
| 3 |
DeepSeek-V4-Pro
DeepSeek
|
80.8%
|
04.06.2026 | Report | Unverified |
| 4 |
DeepSeek-V4-Flash
DeepSeek
|
80.8%
|
04.06.2026 | Report | Unverified |