Aleph Alpha Kolibri vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of Aleph Alpha Kolibri (Aleph Alpha) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
Aleph Alpha Kolibri
Developed by Aleph Alpha · 78.2 Billion Total Parameters (32 routed experts + 2 shared experts) parameters
EU AI Act and GDPR compliant enterprise deployments, European legal and technical translation, 1M context long-document analysis, and 3.46B parameter active inference efficiency.
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 | Aleph Alpha Kolibri | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 62.8% | 62.1% |
| MMLU-Pro | 86.4% | 86.4% |
| MATH-500 | 92.4% | 89.2% |
| Context Window | 1,048,576 tokens (1M) | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.18 | $0.05 |
| Output Pricing (per 1M) | $0.55 | $0.10 |