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text model · Phi-4 · macOS

Can I run Phi-4-reasoning on Apple M3 Pro (18GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~9 tok/s est.

Yes. Phi-4-reasoning runs on Apple M3 Pro (18GB) at Q4_K_M (~10.1 GB of ~12 GB usable).

Needs ~10.1 GB Device usable ~12 GB

Runs at Q4_K_M using ~10.1 GB of ~12 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. Apple M3 Pro (18GB) leaves ~1.9 GB of headroom.

Q4_K_M needed
~10.1 GB
Usable on device
~12 GB
Device memory
18 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~12 GB usable
Q2_K
~7.6 GB
Q3_K_M
~8.5 GB
Q4_K_M
~10.1 GB
Q5_K_M
~11.7 GB
Q6_K
~13.2 GB
Q8_0
~16.2 GB
FP16
~31 GB
The line marks Apple M3 Pro (18GB)'s ~12 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~70 W
Electricity / 1M tokens
~$0.32
Pays for itself after
~7,217M tok

At ~$0.15/kWh and the estimated ~9 tok/s, a million generated tokens costs about $0.32 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,299 Apple M3 Pro (18GB) pays for itself after roughly 7,217 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands macOS

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama
$ ollama run phi4-reasoning:14b
llama.cpp
$ llama-cli -hf bartowski/microsoft_Phi-4-reasoning-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/microsoft_Phi-4-reasoning-GGUF
Model Phi-4
Parameters
14B
Q4_K_M size
8.43 GB
Q8_0 size
14.51 GB
Context
32k
Ollama tag
phi4-reasoning:14b
Full Phi-4-reasoning requirements →
Device macOS
Memory
18 GB unified
Usable for weights
~12 GB
Power draw
~70 W
Best runtime
Ollama (llama.cpp Metal backend) / MLX
Best models for Apple M3 Pro (18GB) →

You could also run

Run Phi-4-reasoning on other hardware

FAQ

Can Apple M3 Pro (18GB) run Phi-4-reasoning?

Yes. Phi-4-reasoning runs on Apple M3 Pro (18GB) at Q4_K_M (~10.1 GB of ~12 GB usable).

How much memory does Phi-4-reasoning need?

Apple M3 Pro (18GB) has room to spare. At Q4_K_M the weights are ~8.43 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.

What is the best tool to run Phi-4-reasoning 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.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.