Anthropic large agent teams tasks
Only in system cards
Internal 24-hour tasks for teams of 1-100 agents: build a company knowledge base, or formalize a theorem in Lean.
New in the Opus 5.5 card. Measures capability and alignment of large agent teams.
Made by Anthropic Released Sep 2026 Multi-agent games Tasks kept private Last in a system card Sep 2026
Last model added Sep 2026
- Level
- Research frontier Researchers, on open problems or tasks that take days
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Agent task Many steps in a terminal, browser, desktop, app, game or robot.
1
System card reports it, from 1 lab
No scores here yet
No lab, leaderboard or Epoch AI run has reported a score for Anthropic large agent teams tasks yet.
Labs report it only in system cards
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 22 Sep 2026 | Claude Opus 5.5 system card | Large agent teams, 24-hour tasks, no overall: knowledge base 0.74 and Lean formalization 0.68 with 100 agents (single agent 0.53 and 0.39), printed on charts, slightly different model version (8.12.3, Figures 8.12.3.A and B) | Capabilities |
More in Games and long tasks
- ARC-AGI-3 In use Interactive game environments where agents must explore, infer goals and rules, and act efficiently without instructions. GPT-6 Astra 100%
- MineDojo Fading Agents complete open-ended tasks in Minecraft, such as mining blocks and fighting mobs, from a large simulation suite. Programmatic checks score many tasks.
Seed2.0 Pro 49% - Orak Fading LLM agents play 12 popular video games across most genres through an MCP interface. Scores come from in-game progress or outcomes per title.
Nemotron 3 Nano 4B 22.9 - GameWorld Only in system cards Multimodal game agents play 34 browser games across 170 tasks. Outcomes are checked from the game state.
Gemini 3 Flash 41.9% - Swarm Bench Only in system cards Models orchestrate agent swarms on complex tasks that benefit from coordinated decomposition and parallel execution. Kimi K3 76.3%
- TextQuests Only in system cards Agents play 25 classic interactive fiction games. Measures game progress and harmful actions per 100 steps.
Muse Spark 2.40