GLM-5-3 (Flagship) vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of GLM-5-3 (Flagship) (Zhipu AI & THUDM) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
GLM-5-3 (Flagship)
Developed by Zhipu AI & THUDM · 744B parameters
Complex algorithmic reasoning, multi-step code synthesis, and long-horizon tool execution.
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 | GLM-5-3 (Flagship) | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 54.8% | 62.1% |
| MMLU-Pro | 78.4% | 86.4% |
| MATH-500 | 93.6% | 89.2% |
| Context Window | 256,000 tokens | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.55 | $0.05 |
| Output Pricing (per 1M) | $2.19 | $0.10 |