Yes — Phi-4 14B (14B) runs at 38 tok/s on M4 with 16 GB RAM using Q4_K_M quantization via Ollama. First token latency is 1.0s. Microsoft's 14B Phi-4 model with strong math and coding performance.
LLMCheck measured Phi-4 14B on M4 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 | 38 tok/s |
| Time to first token | 1.0s |
| Quantization | Q4_K_M |
| Minimum RAM | 16 GB |
| Recommended engine | Ollama |
| Parameters | 14B |
| Benchmark date | 2026-02 |
Q4_K_M 14B Ollama M4
The recommended engine for Phi-4 14B on M4 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 | 62 tok/s | 0.6s | 64 GB | MLX |
| M2 | 28 tok/s | 1.3s | 16 GB | MLX |
To run Phi-4 14B on M4 you need:
See how Phi-4 14B stacks up against other models on your specific Mac hardware.
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