General Agents Benchmark

TauBench V3 Retail

TauBench V3 - Retail domain. Agentic tool use benchmark for retail customer service.

Category

General Agents

Score type

percent

Scale

100%

higher is better

Models tested

4

What is TauBench V3 Retail?

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 Retail 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 Retail 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 Retail test?

TauBench V3 Retail 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 Retail 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 Retail 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-retail/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 4 models tested

Reset
# Model Score Date Source Verified
1 DeepSeek-V4-Flash
DeepSeek
89.1%
04.06.2026 Report Unverified
2 DeepSeek-V4-Pro
DeepSeek
88.9%
04.06.2026 Report Unverified
3 NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
NVIDIA
86.4%
04.06.2026 Report Verified
4 Kimi K2.6
Moonshot AI
82.9%
04.06.2026 Report Unverified

What now?

You've seen how models score on TauBench V3 Retail — here's what to do next.