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🔬New Benchmark Finds Top LLMs Fail at Team Agent Work

TL;DR

AgentWorld tests up to 20 AI agents coordinating through 50+ rounds in a shared MMORPG sandbox, and even the best model tops out at 52% task success. Gemini 3 Flash, Claude Haiku 4.5, GPT-5 Mini and DeepSeek R1-70B all broke down on communication and shared planning.

AgentWorld tests up to 20 AI agents coordinating through 50+ rounds in a shared MMORPG sandbox, and even the best model tops out at 52% task success. Gemini 3 Flash, Claude Haiku 4.5, GPT-5 Mini and DeepSeek R1-70B all broke down on communication and shared planning.

New Benchmark Finds Top LLMs Fail at Team Agent Work — daily-hour-news

Key Points

1

The benchmark covers 100 human-annotated tasks (plus 100 variants) requiring 3 to 20 agents with asymmetric roles to coordinate for 50+ rounds

2

Best result: 52.0% task success, from testing Gemini 3 Flash, Claude Haiku 4.5, GPT-5 Mini and DeepSeek R1-70B

3

A new metric, Causal Collaboration Effectiveness, traces which agent actions actually contributed to the outcome versus wasted effort

4

Failure modes include communication breakdowns, role confusion and agents losing track of shared plans

5

The benchmark and code are fully open-source

Why It Matters

Multi-agent demos look impressive in short clips, but a 52% ceiling on genuine long-horizon teamwork is a reality check for anyone building agent swarms for real enterprise workflows.

Quick Facts

AI agentsbenchmarkmulti-agentGeminiClaudeDeepSeekresearch

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