Gemini 4 Argon vs Aleph Alpha Kolibri
A direct, empirical evaluation of Gemini 4 Argon (Google DeepMind) against Aleph Alpha Kolibri (Aleph Alpha).
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.
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.
| Metric | Gemini 4 Argon | Aleph Alpha Kolibri |
|---|---|---|
| SWE-bench Verified | 78.4% | 62.8% |
| MMLU-Pro | 93.6% | 86.4% |
| MATH-500 | 97.6% | 92.4% |
| Context Window | 2,000,000 tokens | 1,048,576 tokens (1M) |
| Input Pricing (per 1M) | $1.20 | $0.18 |
| Output Pricing (per 1M) | $4.80 | $0.55 |