MLX Benchmark V2 - Coding: leaderboard
Metric: Accuracy (%). Source: huggingface.co. 21 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Sonnet 4.6 | 93.94 |
| 2 | GPT-5.4 Nano | 75.76 |
| 3 | Grok 4.1 Fast | 63.64 |
| 4 | Gemma 4 26B A4B (IT) | 60.61 |
| 5 | Gemini 3 Flash (Preview) | 54.55 |
| 6 | Gemini 2.5 Flash Lite (Preview 09-2025) | 51.52 |
| 7 | DeepSeek V4 Flash | 39.39 |
| 8 | Qwen 3.6 35B A3B | 36.36 |
| 9 | DeepSeek V4 Pro | 35.71 |
| 10 | GPT-5 Nano | 0 |
| 11 | Kimi K2.5 | 0 |
| 12 | Kimi K2.6 | 0 |
| 13 | GLM-5.1 | 0 |
| 14 | Nemotron 3 Ultra | 0 |
Interactive version: theaggregate.ai/benchmark?slug=mlx-benchmark-v2-coding · How It Works · Data refreshed daily, snapshot 2026-09-05.