Yes — Phi-5 Large 28B (28B) runs at 28 tok/s on M4 Pro with 32 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.9s. A capable open-source LLM with 28B parameters.
LLMCheck measured Phi-5 Large 28B on M4 Pro 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 | 28 tok/s |
| Time to first token | 0.9s |
| Quantization | Q4_K_M |
| Minimum RAM | 32 GB |
| Recommended engine | MLX |
| Parameters | 28B |
| Benchmark date | 2026-07 |
Q4_K_M 28B MLX M4 Pro
The recommended engine for Phi-5 Large 28B on M4 Pro is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M5 Max | 38 tok/s | 0.6s | 128 GB | MLX |
| M5 Max | 34 tok/s | 0.7s | 64 GB | Ollama |
| M3 Max | 26 tok/s | 1.1s | 64 GB | Ollama |
To run Phi-5 Large 28B on M4 Pro you need:
Phi-5 Large 28B needs about 32 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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