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- 0.762score
τ²-bench (tau-bench)
Sierra
Simulated customer-service benchmark where an agent follows domain policies and uses tools while a simulated user also acts.
ReferenceAFreshness: A★ 2.3K - 0.701score
MCP-Universe
Salesforce AI Research
Benchmark and framework that tests models and agents on tasks using real-world MCP servers.
ReferenceAFreshness: A★ 602 - 0.684score
GAIA
Meta (FAIR, GenAI), Hugging Face and AutoGPT authors
Benchmark of 450+ real-world questions for general AI assistants, split into three difficulty levels.
ReferenceAFreshness: A - 0.683score
Berkeley Function Calling Leaderboard (BFCL)
Gorilla project, UC Berkeley
Leaderboard that tests how accurately models call functions and tools, from single calls to multi-turn agentic use.
ReferenceDFreshness: D★ 13.1K - 0.581score
MCPMark
EVAL SYS, with LobeHub and NUS TRAIL
Stress test for realistic MCP use across Notion, GitHub, filesystem, PostgreSQL and Playwright servers.
ReferenceCFreshness: C★ 467