Aleph Alpha Kolibri vs Llama 3.3 70B
A direct, empirical evaluation of Aleph Alpha Kolibri (Aleph Alpha) against Llama 3.3 70B (Meta AI).
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.
Llama 3.3 70B
Developed by Meta AI · 70.6B parameters
Self-hosted on-premise deployments and edge dense inference.
| Metric | Aleph Alpha Kolibri | Llama 3.3 70B |
|---|---|---|
| SWE-bench Verified | 62.8% | 38.8% |
| MMLU-Pro | 86.4% | 68.3% |
| MATH-500 | 92.4% | 75.8% |
| Context Window | 1,048,576 tokens (1M) | 128,000 tokens |
| Input Pricing (per 1M) | $0.18 | $0.15 |
| Output Pricing (per 1M) | $0.55 | $0.60 |