Yes — Phi-5 Medium 14B (14B) runs at 24 tok/s on M2 with 16 GB RAM using Q4_K_M quantization via Ollama. First token latency is 1.4s. A capable open-source LLM with 14B parameters.
LLMCheck measured Phi-5 Medium 14B on M2 using the standard methodology: Q4_K_M quantization, 256-token input, 512-token output, 3 runs averaged on a freshly-booted system.
| Metric | Value |
|---|---|
| Tokens per second | 24 tok/s |
| Time to first token | 1.4s |
| Quantization | Q4_K_M |
| Minimum RAM | 16 GB |
| Recommended engine | Ollama |
| Parameters | 14B |
| Benchmark date | 2026-06 |
Q4_K_M 14B Ollama M2
The recommended engine for Phi-5 Medium 14B on M2 is Ollama. Install Ollama, then pull the model:
Ollama handles quantization automatically — it will download the Q4_K_M variant (~16 GB) and start an interactive chat session.
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 65 tok/s | 0.5s | 128 GB | MLX |
| M5 Max | 58 tok/s | 0.6s | 64 GB | Ollama |
| M4 Pro | 48 tok/s | 0.7s | 24 GB | MLX |
| M3 | 32 tok/s | 1.1s | 16 GB | Ollama |
To run Phi-5 Medium 14B on M2 you need:
See how Phi-5 Medium 14B stacks up against other models on your specific Mac hardware.
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