Coding · benchmark vs real usage
Best AI model for coding: benchmarks vs. what developers use
On coding benchmarks, Claude Opus 5 (batch) leads with a coding index of 78. But in real production traffic across file I/O, debugging, code review, and code generation tasks, DeepSeek: DeepSeek V4 Flash 0423 handles the largest share at 27.4%- measured directly from OpenRouter's task-classified traffic, not a benchmark opinion.
- #1 DeepSeek: DeepSeek V4 Flash 0423 - 27.4% of coding traffic · coding index 69.1
- #2 Z.ai: GLM 5.2 (batch) - 13.7% of coding traffic · coding index 68.8
- #3 Xiaomi: MiMo-V2.5 - 13.2% of coding traffic · coding index 56.8
- #4 OpenAI: GPT-5.6 Luna (batch) - 11.1% of coding traffic · coding index 71.4
- #5 Tencent: Hy3 - 9.4% of coding traffic
- #6 DeepSeek: DeepSeek V4 Pro - 9.4% of coding traffic · coding index 59.4
- #7 Google: Gemini 3.6 Flash (batch) - 4.3% of coding traffic · coding index 69.2
- #8 Poolside: Laguna S 2.1 (free) - 3.6% of coding traffic
- #9 NVIDIA: Nemotron 3 Ultra (free) - 2.2% of coding traffic · coding index 49.3
- #10 StepFun: Step 3.7 Flash - 1.7% of coding traffic · coding index 39.6
- #11 Claude Opus 5 (batch) - 1.2% of coding traffic · coding index 78
- #12 MiniMax: MiniMax M3 (batch) - 1.0% of coding traffic · coding index 58.6
- #13 Anthropic: Claude Opus 4.7 (batch) - 0.6% of coding traffic · coding index 73.6
- #14 MoonshotAI: Kimi K3 - 0.4% of coding traffic · coding index 76.2
- #15 Anthropic: Claude Sonnet 5 (batch) - 0.3% of coding traffic · coding index 71.5
| # | Model | Coding traffic share | Coding index |
|---|---|---|---|
| 01 | DeepSeek: DeepSeek V4 Flash 0423 | 27.4% | 69.1 |
| 02 | Z.ai: GLM 5.2 (batch) | 13.7% | 68.8 |
| 03 | Xiaomi: MiMo-V2.5 | 13.2% | 56.8 |
| 04 | OpenAI: GPT-5.6 Luna (batch) | 11.1% | 71.4 |
| 05 | Tencent: Hy3 | 9.4% | - |
| 06 | DeepSeek: DeepSeek V4 Pro | 9.4% | 59.4 |
| 07 | Google: Gemini 3.6 Flash (batch) | 4.3% | 69.2 |
| 08 | Poolside: Laguna S 2.1 (free) | 3.6% | - |
| 09 | NVIDIA: Nemotron 3 Ultra (free) | 2.2% | 49.3 |
| 10 | StepFun: Step 3.7 Flash | 1.7% | 39.6 |
| 11 | Claude Opus 5 (batch) | 1.2% | 78 |
| 12 | MiniMax: MiniMax M3 (batch) | 1.0% | 58.6 |
| 13 | Anthropic: Claude Opus 4.7 (batch) | 0.6% | 73.6 |
| 14 | MoonshotAI: Kimi K3 | 0.4% | 76.2 |
| 15 | Anthropic: Claude Sonnet 5 (batch) | 0.3% | 71.5 |
| 16 | OpenAI: GPT-5.6 Terra (batch) | 0.3% | 76.7 |
| 17 | Z.ai: GLM 5 | 0.2% | - |
| 18 | Anthropic: Claude Haiku 4.5 (batch) | 0.1% | 43.9 |
Coding traffic share is a weighted rollup of OpenRouter's real classified traffic across nine coding-task categories (file I/O, repo scanning, frontend/UI, DevOps config, shell execution, SQL/database, debugging, code review, code generation), weighted by each category's own share of total classified traffic.
Frequently asked questions
What is the best AI model for coding?
On benchmarks, Claude Opus 5 (batch) leads coding tasks with a coding index of 78. In real usage, DeepSeek: DeepSeek V4 Flash 0423 handles the largest share of actual coding traffic (27%).
What model do developers actually use for coding?
DeepSeek: DeepSeek V4 Flash 0423 handles 27.4% of real coding-task traffic on OpenRouter, measured across file I/O, debugging, code review, and code generation tasks.
