Llama 3.3 70B vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of Llama 3.3 70B (Meta AI) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
Llama 3.3 70B
Developed by Meta AI · 70.6B parameters
Self-hosted on-premise deployments and edge dense inference.
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 | Llama 3.3 70B | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 38.8% | 62.1% |
| MMLU-Pro | 68.3% | 86.4% |
| MATH-500 | 75.8% | 89.2% |
| Context Window | 128,000 tokens | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.15 | $0.05 |
| Output Pricing (per 1M) | $0.60 | $0.10 |