Microsoft vs Meta small models
Phi-4 wins on benchmarks, Llama wins on context and creativity. Both are excellent small models.
Choose Phi-4 for reasoning, math, and when you need MIT licensing.
Choose Llama 8B for long context, creative writing, and chat applications.
Phi-4 is Microsoft's remarkably efficient small model. How does it compare to Llama 3 at similar sizes?
| Specification | Phi-4 14B | Llama 3.1 8B |
|---|---|---|
| Developer | Microsoft | Meta |
| Parameters | 14B | 8B |
| Context Length | 16K | 128K |
| VRAM (Minimum) | 8GB (Q4) | 6GB (Q4) |
| VRAM (Recommended) | 12GB | 8GB |
| Release Date | December 2024 | July 2024 |
| License | MIT | Llama 3.1 Community License |
| Category | Phi-4 14B | Llama 3.1 8B | Winner |
|---|---|---|---|
| MMLU | 78.0% | 69.4% | Phi-4 14B |
| Math (GSM8K) | 89.0% | 84.5% | Phi-4 14B |
| Context Length | 16K | 128K | Llama 3.1 8B |
| Creative Writing | Good | Very Good | Llama 3.1 8B |
| License | MIT | Community | Phi-4 14B |
Check our GPU buying guides to find the right hardware for running LLMs locally.