ConvAI Laya vs Visual Jev (Qwen3-VL 8B Backbone)
A direct, empirical evaluation of ConvAI Laya (ConvAI Innovations (Vishal Mysore / visrow)) against Visual Jev (Qwen3-VL 8B Backbone) (Independent AI Systems Lab (Guanxu Yu & Yuhang Yao)).
ConvAI Laya
Developed by ConvAI Innovations (Vishal Mysore / visrow) · 421 Million (ModernBERT-large Backbone) parameters
Client-side in-browser decision execution via WebGPU/WASM, zero-cost operational routing, private on-device medical/financial triage, and domain-specific fine-tuning.
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 | ConvAI Laya | Visual Jev (Qwen3-VL 8B Backbone) |
|---|---|---|
| SWE-bench Verified | 64.2% | 62.1% |
| MMLU-Pro | 82.4% | 86.4% |
| MATH-500 | 88.5% | 89.2% |
| Context Window | 8,192 tokens | 32,768 tokens (Visual prefix + batched question suffixes) |
| Input Pricing (per 1M) | $0.00 | $0.05 |
| Output Pricing (per 1M) | $0.00 | $0.10 |