- Organizations
- Sierra
Sierra: AI benchmarks & research
Conversational AI agent company. Maintains the tau-bench family of tool-agent-user benchmarks.
Maintained by Sierra
12 benchmarks- t2-bench
t2-bench is a benchmark for evaluating agentic tool use capabilities, measuring how well models can select, sequence, and utilize tools to solve complex tasks. It tests autonomous planning and execution in multi-step scenarios.
- Leader
Gemini 3.1 Pro99.3%
- Models scored
- 23
- Tau2 Airline
TAU2 airline domain benchmark for evaluating conversational agents in dual-control environments where both AI agents and users interact with tools in airline customer service scenarios. Tests agent coordination, communication, and ability to guide user actions in tasks like flight booking, modifications, cancellations, and refunds.
- Leader
Muse Glimmer-30B78.0%
- Models scored
- 26
- Tau2 Retail
τ²-bench retail domain evaluates conversational AI agents in customer service scenarios within a dual-control environment where both agent and user can interact with tools. Tests tool-agent-user interaction, rule adherence, and task consistency in retail customer support contexts.
- Leader
Claude Opus 4.691.9%
- Models scored
- 28
- Tau2 Telecom
τ²-Bench telecom domain evaluates conversational agents in a dual-control environment modeled as a Dec-POMDP, where both agent and user use tools in shared telecommunications troubleshooting scenarios that test coordination and communication capabilities.
- Leader
Claude Opus 4.699.3%
- Models scored
- 37
- Tau3 Airline
τ³-Bench airline domain evaluates agentic models on multi-turn, tool-using customer-support scenarios in a simulated airline booking and reservations environment.
- Leader
Mistral Medium 3.572.0%
- Models scored
- 1
- Tau3 Banking
τ³-Bench banking domain evaluates agentic models on multi-turn, tool-using customer-support scenarios in a simulated retail banking environment.
- Leader
Ling 3.0 Flash Fin41.0%- Models scored
- 21
- TAU3-Bench
TAU3-Bench is a benchmark for evaluating general-purpose agent capabilities, testing models on multi-turn interactions with simulated user models, retrieval, and complex decision-making scenarios.
- Leader
GPT-Live-186.2%
- Models scored
- 10
- Tau3 Retail
τ³-Bench retail domain evaluates agentic models on multi-turn, tool-using customer-support scenarios in a simulated online retail environment.
- Leader
Mistral Medium 3.576.1%
- Models scored
- 1
- Tau3 Telecom
τ³-Bench telecom domain evaluates agentic models on multi-turn, tool-using customer-support and troubleshooting scenarios in a simulated telecommunications environment.
- Leader
Mistral Medium 3.591.4%
- Models scored
- 1
- Tau-bench
τ-bench: A benchmark for tool-agent-user interaction in real-world domains. Tests language agents' ability to interact with users and follow domain-specific rules through dynamic conversations using API tools and policy guidelines across retail and airline domains. Evaluates consistency and reliability of agent behavior over multiple trials.
- Leader
Step-3.5-Flash88.2%
- Models scored
- 6
- TAU-bench Airline
Part of τ-bench (TAU-bench), a benchmark for Tool-Agent-User interaction in real-world domains. The airline domain evaluates language agents' ability to interact with users through dynamic conversations while following domain-specific rules and using API tools. Agents must handle airline-related tasks and policies reliably.
- Leader
Claude Sonnet 4.570.0%
- Models scored
- 23
- TAU-bench Retail
A benchmark for evaluating tool-agent-user interaction in retail environments. Tests language agents' ability to handle dynamic conversations with users while using domain-specific API tools and following policy guidelines. Evaluates agents on tasks like order cancellations, address changes, and order status checks through multi-turn conversations.
- Leader
Claude Sonnet 4.586.2%
- Models scored
- 25