AgentBench

AgentBench is the first benchmark designed to evaluate LLM-as-Agent across a diverse spectrum of environments. It bundles 8 environments — 5 newly created (Operating System, Database, Knowledge Graph, Digital Card Game, Lateral Thinking Puzzles) and 3 adapted (House-Holding from ALFWorld, Web Shopping from WebShop, Web Browsing from Mind2Web). The benchmark requires roughly 4,000 dev-set and 13,000 test-set interactions per model.

GitHub

Work with this as data

Every API here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for apis

7 MCP tools reach this
  • find_apisBrowse and filter every API in the catalog.
  • get_api_artifactsOne API's artifacts, grouped by type.
  • get_openapiThe primary OpenAPI for this API.
  • find_similar_apisAPIs that look like this one.
  • apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
  • resolveTurn a domain, URL or GitHub org into the provider it belongs to.
  • find_cohortsEvery scored population of providers in the catalog.
All 92 tools →

Call it yourself

curl for this page
This API
curl "https://apis.io/api/v1/apis/evals:agentbench"
All apis
curl "https://apis.io/api/v1/apis?limit=25"

Calls without X-API-Key need no key. Calls with it need a paid plan — get a key.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

A second provider on the same verified email joins the account you already have.

API entry from apis.yml

apis.yml Raw ↑
name: AgentBench
description: AgentBench is the first benchmark designed to evaluate LLM-as-Agent across a diverse spectrum
  of environments. It bundles 8 environments — 5 newly created (Operating System, Database, Knowledge
  Graph, Digital Card Game, Lateral Thinking Puzzles) and 3 adapted (House-Holding from ALFWorld, Web
  Shopping from WebShop, Web Browsing from Mind2Web). The benchmark requires roughly 4,000 dev-set and
  13,000 test-set interactions per model.
humanURL: https://github.com/THUDM/AgentBench
baseURL: https://github.com/THUDM/AgentBench
tags:
- Benchmarks
- AI Agents
- Multi-Environment
- LLM-as-Agent
- Tsinghua
tags_raw:
- Benchmark
- AI Agents
- Multi-Environment
- LLM-as-Agent
- Tsinghua
properties:
- type: GitHubRepository
  url: https://github.com/THUDM/AgentBench
- type: Paper
  url: https://arxiv.org/abs/2308.03688
- type: Leaderboard
  url: https://llmbench.ai/agent