ConvAI Laya vs Gemini 4 Argon
A direct, empirical evaluation of ConvAI Laya (ConvAI Innovations (Vishal Mysore / visrow)) against Gemini 4 Argon (Google DeepMind).
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.
Gemini 4 Argon
Developed by Google DeepMind · Frontier Coding & Security Engine on TPU v6e Ironclad parameters
Automated GitHub issue resolution (78.4% SWE-bench Verified), cybersecurity exploit auditing (91.4% CyberSecBench), 2M token context buffer, and aggressive $1.20/$4.80 API pricing.
| Metric | ConvAI Laya | Gemini 4 Argon |
|---|---|---|
| SWE-bench Verified | 64.2% | 78.4% |
| MMLU-Pro | 82.4% | 93.6% |
| MATH-500 | 88.5% | 97.6% |
| Context Window | 8,192 tokens | 2,000,000 tokens |
| Input Pricing (per 1M) | $0.00 | $1.20 |
| Output Pricing (per 1M) | $0.00 | $4.80 |