GPT-6 Luna vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of GPT-6 Luna (OpenAI) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
GPT-6 Luna
Developed by OpenAI · Proprietary High-Throughput Distillation parameters
High-throughput document extraction, sub-second routing, customer service triage, code autocomplete, and cost-optimized reasoning via Luna Pro mode.
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 | GPT-6 Luna | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 48.2% | 62.1% |
| MMLU-Pro | 74.6% | 86.4% |
| MATH-500 | 84.1% | 89.2% |
| Context Window | 1,050,000 tokens | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.10 | $0.05 |
| Output Pricing (per 1M) | $0.50 | $0.10 |