Beyond the All-in-One Agent: leaderboard
Large language model (LLM) agents are increasingly expected to operate in enterprise environments, where work is distributed across specialized roles, permission-controlled systems, and cross-departmental procedures. However, existing enterprise benchmarks largely evaluate single agents with broad tool access, while existing multi-agent benchmarks rarely capture realistic enterprise constraints su
Metric: avg. (self-reported). Source: benchmarklist.com. Saturation forecast: Around June 2027. 12 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | DeepSeek V4 Pro | 62 | #102 |
| 2 | DeepSeek V4 Flash | 57.33 | #137 |
| 3 | Claude Sonnet 4.6 | 52.67 | #90 |
| 4 | Gemini 3.1 Pro (Preview) | 47.67 | #58 |
| 5 | GPT-5.4 | 42.33 | #79 |
| 6 | Qwen 3.5 122B A10B | 33.33 | #173 |
| 7 | GPT-5 Mini | 32 | #186 |
| 8 | Qwen 3.5 35B A3B | 31 | #256 |
| 9 | MiniMax-M2.7 | 24.67 | #258 |
| 10 | Gemini 3.1 Flash Lite (Preview) | 16.67 | #194 |
| 11 | MiMo-V2-Flash | 16.67 | #372 |
| 12 | Qwen 3.5 9B | 7.67 | #379 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=beyond-the-all-in-one-agent · How It Works · Data refreshed daily, snapshot 2026-10-20.