Agentic · benchmark vs real usage
Best AI model for agents: benchmarks vs. real agentic traffic
On agentic benchmarks, Anthropic: Claude Fable 5.1 (batch) leads with an agentic index of 57.2. But agent benchmarks are widely known to be gameable - in real production traffic across tool dispatch, workflow execution, planning, memory, and web search, DeepSeek: DeepSeek V4.1 Flash (batch) handles the largest share at 44.3%.
- #1 DeepSeek: DeepSeek V4.1 Flash (batch) - 44.3% of agentic traffic
- #2 Z.ai: GLM 5.3 Flash (batch) - 24.0% of agentic traffic · agentic index 50.9
- #3 OpenAI: GPT-6 Luna (batch) - 10.7% of agentic traffic
- #4 Anthropic: Claude Haiku 5.5 (batch) - 4.4% of agentic traffic
- #5 OpenAI: GPT-6.1 Sol (batch) - 3.0% of agentic traffic
- #6 OpenAI: GPT-5.6 Luna (batch) - 2.7% of agentic traffic · agentic index 42.1
- #7 MiniMax: MiniMax M3.1 Flash - 2.6% of agentic traffic
- #8 Z.ai: GLM 5.3 (batch) - 2.6% of agentic traffic · agentic index 53.1
- #9 Tencent: Hy4 preview - 2.3% of agentic traffic
- #10 DeepSeek: DeepSeek V4 Flash 0423 - 1.8% of agentic traffic · agentic index 41
- #11 Google: Gemini 3.1 Flash Lite (batch) - 0.5% of agentic traffic
- #12 Google: Gemma 4 26B A4B (free) - 0.4% of agentic traffic · agentic index 2.9
- #13 OpenAI: gpt-oss-20b (batch) - 0.3% of agentic traffic · agentic index 1.2
- #14 OpenAI: GPT-4o-mini (batch) - 0.2% of agentic traffic
- #15 OpenAI: GPT-5.6 Terra (batch) - 0.1% of agentic traffic · agentic index 43.2
| # | Model | Agentic traffic share | Agentic index |
|---|---|---|---|
| 01 | DeepSeek: DeepSeek V4.1 Flash (batch) | 44.3% | - |
| 02 | Z.ai: GLM 5.3 Flash (batch) | 24.0% | 50.9 |
| 03 | OpenAI: GPT-6 Luna (batch) | 10.7% | - |
| 04 | Anthropic: Claude Haiku 5.5 (batch) | 4.4% | - |
| 05 | OpenAI: GPT-6.1 Sol (batch) | 3.0% | - |
| 06 | OpenAI: GPT-5.6 Luna (batch) | 2.7% | 42.1 |
| 07 | MiniMax: MiniMax M3.1 Flash | 2.6% | - |
| 08 | Z.ai: GLM 5.3 (batch) | 2.6% | 53.1 |
| 09 | Tencent: Hy4 preview | 2.3% | - |
| 10 | DeepSeek: DeepSeek V4 Flash 0423 | 1.8% | 41 |
| 11 | Google: Gemini 3.1 Flash Lite (batch) | 0.5% | - |
| 12 | Google: Gemma 4 26B A4B (free) | 0.4% | 2.9 |
| 13 | OpenAI: gpt-oss-20b (batch) | 0.3% | 1.2 |
| 14 | OpenAI: GPT-4o-mini (batch) | 0.2% | - |
| 15 | OpenAI: GPT-5.6 Terra (batch) | 0.1% | 43.2 |
Agentic traffic share is a weighted rollup of OpenRouter's real classified traffic across five agentic-task categories (tool dispatch, workflow execution, multi-step planning, memory extraction, web search), weighted by each category's own share of total classified traffic.
Frequently asked questions
What is the best AI model for agents?
On benchmarks, Anthropic: Claude Fable 5.1 (batch) leads agentic tasks with an agentic index of 57.2. In real usage, DeepSeek: DeepSeek V4.1 Flash (batch) handles the largest share of actual agentic traffic (44%).
Are agent benchmarks reliable?
Agent benchmarks are widely criticized as gameable and inconsistent across labs. Real production usage - what developers actually route agentic workloads to - is a harder-to-game complement to benchmark scores.