MMStar — Vision-language benchmark curated to reduce data leakage.
| # | Model | Vendor | Best score | Runs | Last seen |
|---|---|---|---|---|---|
| 1 | Qwen3.5 397B A17B | Alibaba | 83.8 | 1 | 2026-08-24 |
| 2 | Qwen3.6 Plus | Alibaba | 83.3 | 1 | 2026-08-23 |
| 3 | Qwen3.5 122B A10B | Alibaba | 82.9 | 1 | 2026-08-23 |
| 4 | Qwen3.5 35B A3B | Alibaba | 81.9 | 1 | 2026-08-23 |
| 5 | Qwen3.6 27B | Alibaba | 81.4 | 2 | 2026-08-24 |
| 6 | Qwen3.5 27B | Alibaba | 81 | 2 | 2026-08-24 |
| 7 | Qwen3 VL 32B Reasoning | Alibaba | 79.4 | 1 | 2026-08-23 |
| 8 | Gemini 2.5 Pro | 79.2 | 2 | 2026-06-05 | |
| 9 | Qwen3 VL 235B A22B Reasoning | Alibaba | 78.7 | 2 | 2026-08-23 |
| 10 | Qwen3 VL 235B A22B Instruct | Alibaba | 78.4 | 1 | 2026-08-23 |
| 11 | Qwen3 VL 32B Instruct | Alibaba | 77.7 | 1 | 2026-08-23 |
| 12 | Step3 VL 10B | StepFun | 77.6 | 2 | 2026-06-05 |
| 13 | Gemma 4 31B | 77.3 | 1 | 2026-08-24 | |
| 14 | Qwen3 VL 30B A3B Reasoning | Alibaba | 75.5 | 1 | 2026-08-23 |
| 15 | Qwen3 VL Thinking (8B) | Alibaba | 75.3 | 3 | 2026-08-23 |
| 16 | GLM-4.6V (106B-A12B) | Z.ai | 75.3 | 2 | 2026-06-05 |
| 17 | GLM-4.6V-Flash (9B) | Z.ai | 74.3 | 2 | 2026-06-05 |
| 18 | Qwen3 VL 4B (Reasoning) | Alibaba | 73.2 | 2 | 2026-08-23 |
| 19 | Claude Opus 4.5 | Anthropic | 73.2 | 1 | 2026-08-24 |
| 20 | MiMo VL RL 2508 (7B) | Xiaomi | 72.9 | 2 | 2026-06-05 |
| 21 | Qwen3 VL 30B A3B Instruct | Alibaba | 72.1 | 1 | 2026-08-23 |
| 22 | Qwen3 VL 8B Instruct | Alibaba | 70.9 | 1 | 2026-08-23 |
| 23 | Qwen2.5 VL 72B | Alibaba | 70.8 | 1 | 2026-08-23 |
| 24 | InternVL-3.5 (8B) | OpenGVLab | 69.8 | 2 | 2026-06-05 |
| 25 | Qwen3 VL 4B Instruct | Alibaba | 69.8 | 1 | 2026-08-23 |
| 26 | Qwen2.5 VL 32B | Alibaba | 69.5 | 1 | 2026-08-23 |
| 27 | Qwen2-VL-72B-Instruct | Alibaba | 68.3 | 1 | 2026-08-24 |
| 28 | Mage-VL-4B | Microsoft | 67.3 | 1 | 2026-07-26 |
| 29 | Qwen2.5 Omni 7B | Alibaba | 64 | 1 | 2026-08-23 |
| 30 | GPT-4o | OpenAI | 63.9 | 1 | 2026-08-24 |
| 31 | LFM2.5-VL-3B | Liquid AI | 63.3 | 3 | 2026-08-23 |
| 32 | Claude 3.5 Sonnet | Anthropic | 62.2 | 1 | 2026-08-24 |
| 33 | Phi 4 MM 5.6B | Microsoft | 61.2 | 1 | 2026-07-26 |
| 34 | InternVL3-2B | OpenGVLab | 61.1 | 1 | 2026-08-09 |
| 35 | Phi 4 R V 15B | Microsoft | 59.6 | 1 | 2026-07-26 |
| 36 | Gemma 4 E2B | 57.9 | 1 | 2026-08-12 | |
| 37 | LFM2-VL-3B | Liquid AI | 57.7 | 2 | 2026-08-22 |
| 38 | LFM2-VL-3B (3.1B) | Liquid AI | 57.7 | 1 | 2026-08-12 |
| 39 | InternVL3_5-2B | OpenGVLab | 57.7 | 1 | 2026-08-09 |
| 40 | Qwen2.5 VL 3B | Alibaba | 56.1 | 1 | 2026-08-09 |
| 41 | North-Micro-Vision-Instruct | Cohere | 51.8 | 1 | 2026-08-23 |
| 42 | LFM2.5-VL-1.6B | Liquid AI | 50.7 | 1 | 2026-08-09 |
| 43 | InternVL3.5-1B | OpenGVLab | 50.3 | 1 | 2026-08-09 |
| 44 | LFM2-VL-1.6B | Liquid AI | 49.9 | 1 | 2026-08-09 |
| 45 | LFM2.5-VL-450M-Extract | Liquid AI | 43 | 1 | 2026-08-09 |
| 46 | LFM2-VL-450M | Liquid AI | 40.9 | 1 | 2026-08-09 |
Best tracked score per model (default configuration; source-attributed and verification-tiered). Open a model for its full benchmark surface, provenance and pricing.