Can Phi-4 14B run on MacBook Pro M3 Pro 36GB?

YES — Runs Great

A81Great

Estimated from fit model

Phi-4 14B needs ~16.4 GB VRAM. MacBook Pro M3 Pro 36GB has 25.9 GB. With Q4_K_M quantization, expect ~14 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 16.4 GB, 13.8 tok/s, Runs well

16.4 GB required25.9 GB available

63% VRAM used

Fit status

Runs well

Decode

13.8 tok/s

TTFT

14046 ms

Safe context

16K

Memory

16.4 GB / 25.9 GB

Memory breakdown

Weights8.5 GB

KV Cache3.1 GB

Runtime0.9 GB

Headroom3.9 GB

See how fast it feels

See how fast it feelsPhi-4 14B on MacBook Pro M3 Pro 36GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 13.8 tok/s decode · 14.0s TTFT (warm) · 35 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Shared-memory contention still exists

The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	13.8 tok/s	7661 ms	16K
Coding	A	Runs well	13.8 tok/s	14046 ms	16K
Agentic Coding	A	Runs well	13.8 tok/s	20430 ms	16K
Reasoning	A	Runs well	13.8 tok/s	16599 ms	16K
RAG	A	Runs well	13.8 tok/s	25537 ms	16K

Quantization options

How Phi-4 14B (14B params) fits at each quantization level on MacBook Pro M3 Pro 36GB (25.9 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	A77
Q3_K_S	3	6.9 GB	Low	A78
NVFP4	4	7.8 GB	Medium	A78
Q4_K_M	4	8.5 GB	Medium	A79
Q5_K_M	5	10.1 GB	High	A79
Q6_K	6	11.5 GB	High	A80
Q8_0Best for your GPU	8	15.0 GB	Very High	A82
F16	16	28.7 GB	Maximum	F0

Get started

Copy-paste commands to run Phi-4 14B on your machine.

Run

ollama run phi4

Your hardware

More models your MacBook Pro M3 Pro 36GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	16.6 tok/s
Qwen 3.5 27B	27B	S	7.2 tok/s
Qwen 3.6 27B	27B	S	5.5 tok/s
Qwen 3.6 35B A3B	35B	A	12.1 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	17.1 tok/s

Frequently asked questions

Can MacBook Pro M3 Pro 36GB run Phi-4 14B?

Yes, MacBook Pro M3 Pro 36GB can run Phi-4 14B with a A grade (Runs well). Expected decode speed: 13.8 tok/s.

How much VRAM does Phi-4 14B need?

Phi-4 14B (14B parameters) requires approximately 16.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi-4 14B?

The recommended quantization for Phi-4 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi-4 14B run at on MacBook Pro M3 Pro 36GB?

On MacBook Pro M3 Pro 36GB, Phi-4 14B achieves approximately 13.8 tokens per second decode speed with a time-to-first-token of 14046ms using Q4_K_M quantization.

Can MacBook Pro M3 Pro 36GB run Phi-4 14B for coding?

For coding workloads, Phi-4 14B on MacBook Pro M3 Pro 36GB receives a A grade with 13.8 tok/s and 16K context.

What context window can Phi-4 14B use on MacBook Pro M3 Pro 36GB?

On MacBook Pro M3 Pro 36GB, Phi-4 14B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M3 Pro 36GB as fast as VRAM for Phi-4 14B?

Not always. MacBook Pro M3 Pro 36GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.

See all results for MacBook Pro M3 Pro 36GB See all hardware for Phi-4 14B

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