Xiaomi MiMo-V2.6 Flash vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of Xiaomi MiMo-V2.6 Flash (Xiaomi AI Lab) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
Xiaomi MiMo-V2.6 Flash
Developed by Xiaomi AI Lab · 185 Billion (Sparse MoE) parameters
Low-latency agent loops, high-volume classification, and developer code completion.
Visual Jev (Qwen3-VL 8B Backbone)
Developed by Independent AI Systems Lab (Guanxu Yu & Yuhang Yao) · 8.2 Billion Vision-Language Parameters parameters
Sub-20ms multi-query image verification, automated rejection sampling in generative diffusion pipelines (FLUX / SD3), robotics perception routing, and high-frequency visual software inspection.
| Metric | Xiaomi MiMo-V2.6 Flash | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 64.2% | 62.1% |
| MMLU-Pro | 82.4% | 86.4% |
| MATH-500 | 89.5% | 89.2% |
| Context Window | 128,000 tokens | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.04 | $0.05 |
| Output Pricing (per 1M) | $0.08 | $0.10 |