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text model · phi · macOS

Can I run Phi-4 14B on Apple M5 Pro (48GB)?

Compatibility verdict VRAM threshold engine
Yes, it runsGPU accelerated

Yes. Phi-4 14B runs on Apple M5 Pro (48GB) at Q4_K_M (~10.8 GB of ~32 GB usable).

Needs ~10.8 GB Device usable ~32 GB

Runs at Q4_K_M using ~10.8 GB of ~32 GB usable. You have room for FP16 for higher quality.

Q4_K_M needed
~10.8 GB
Usable on device
~32 GB
Device memory
48 GB
Best quant
Q4_K_M

Run it

Install commands macOS

Pick your tool. All three load the same Q4_K_M weights.

Ollama
$ ollama run phi4:14b
llama.cpp
$ llama-cli -hf bartowski/phi-4-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/phi-4-GGUF

vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

Model phi
Parameters
14B
Q4_K_M size
9.05 GB
Q8_0 size
15.58 GB
Context
16k
Ollama tag
phi4:14b
Full Phi-4 14B requirements →
Device macOS
Memory
48 GB unified
Usable for weights
~32 GB
Best runtime
MLX direct / Ollama (MLX backend)
Best models for Apple M5 Pro (48GB) →

You could also run

Run Phi-4 14B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)16GB RAM Laptop (CPU/iGPU only)iPad Pro M4 (16GB, 1TB/2TB config)

FAQ

Can Apple M5 Pro (48GB) run Phi-4 14B?

Yes. Phi-4 14B runs on Apple M5 Pro (48GB) at Q4_K_M (~10.8 GB of ~32 GB usable).

How much memory does Phi-4 14B need?

Apple M5 Pro (48GB) has room to spare. At Q4_K_M the weights are ~9.05 GB; with KV cache and runtime overhead, budget ~10.8 GB at a 4k context.

What is the best tool to run Phi-4 14B on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

Sources

Memory figures are estimates. See methodology.