AgentWorldBenchBrowse 296

AgentWorldBench

Can the model plan, use tools, and finish a multi-step task?

Version not specifiedExact reported variant
Agents4 ranked models5 reported values1 reportsHigher is better

Top rankings

One row per model, using its best reported score across effort settings.

4
RankModelBest scoreBest reported setting
1Qwen-AgentWorld-397B-A17BQwen58.71Reported configurationQwen report1 value · 1 reportJun 22, 2026 · source
2GPT-5.4OpenAI58.25Reported configurationQwen report1 value · 1 reportJun 22, 2026 · source
3Qwen3.5-35B-A3BQwen56.39Reported configurationQwen report2 values · 1 reportJun 22, 2026 · source
4Claude Sonnet 4.6Anthropic56.04Reported configurationQwen report1 value · 1 reportJun 22, 2026 · source

Effort curve

Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.

0
No cost-linked effort sweep for this version.
Definition and comparison boundarylimited methodology

Can the model plan, use tools, and finish a multi-step task?

Agentic execution across tools, environments, or long-running workflows. Higher is better. This benchmark reports points rather than percent correct.

Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.

Five-dimensional rubric mean across Qwen's seven-domain AgentWorldBench; Qwen states the 35B pipeline result as 47.73 → 56.39.

Method / source