General Agents Benchmark

AgentWorldBench Overall

AgentWorldBench Overall - mean across all 7 agent interaction domains (MCP, Search, Terminal, SWE, Android, Web, OS). Five-dimensional rubric, normalized to 0-100.

Category

General Agents

Score type

percent

Scale

100%

higher is better

Models tested

4

What is AgentWorldBench Overall?

AgentWorldBench Overall is a benchmark for how well a model acts as a general-purpose agent. The official description says: "AgentWorldBench Overall - mean across all 7 agent interaction domains (MCP, Search, Terminal, SWE, Android, Web, OS)". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

AgentWorldBench Overall measures how well a model acts as a general-purpose agent. In detail, it checks:

  • solving long, multi-step tasks with many intermediate decisions
  • using tools correctly (browsers, terminals, APIs, calendars, other apps)
  • adapting when something unexpected happens mid-task
  • staying on goal over long task horizons instead of wandering off

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.

Official methodology note: AgentWorldBench Overall - mean across all 7 agent interaction domains (MCP, Search, Terminal, SWE, Android, Web, OS). Five-dimensional rubric, normalized to 0-100.

Frequently asked questions

What is the AgentWorldBench Overall benchmark?

AgentWorldBench Overall is a benchmark for how well a model acts as a general-purpose agent. The official description says: 'AgentWorldBench Overall - mean across all 7 agent interaction domains (MCP, Search, Terminal, SWE, Android, Web, OS)'. Below we describe in simple words what benchmarks of this type generally examine.

What does AgentWorldBench Overall test?

AgentWorldBench Overall mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: solving long, multi-step tasks with many intermediate decisions; using tools correctly (browsers, terminals, APIs, calendars, other apps); adapting when something unexpected happens mid-task.

How is the AgentWorldBench Overall 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 AgentWorldBench Overall data and scores?

The official source is https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B. 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/agentworldbench-overall/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 Qwen-AgentWorld-35B-A3B
Qwen Team (Alibaba Cloud)
56.39%
24.06.2026 Qwen Team (official model card) Verified
2 Kimi K2.6
Moonshot AI
53.42%
24.06.2026 Qwen Team (official model card - comparison) Unverified
3 DeepSeek-V4-Pro
DeepSeek
52.97%
24.06.2026 Qwen Team (official model card - comparison) Unverified
4 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
47.73%
24.06.2026 Qwen Team (official model card - comparison) Unverified

What now?

You've seen how models score on AgentWorldBench Overall — here's what to do next.