Will It Run AI

Can Phi-4-reasoning-plus 14B run on MacBook Pro M2 Pro 32GB?

YES — Runs Great

S91Excellent
Estimated from fit model

Phi-4-reasoning-plus 14B needs ~16.4 GB VRAM. MacBook Pro M2 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~17 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
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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, 16.8 tok/s, Runs well
16.4 GB required23.0 GB available
71% VRAM used

Fit status

Runs well

Decode

16.8 tok/s

TTFT

11535 ms

Safe context

33K

Memory

16.4 GB / 23.0 GB

Memory breakdown

Weights9.0 GB
KV Cache3.1 GB
Runtime0.9 GB
Headroom3.5 GB

See how fast it feels

See how fast it feelsPhi-4-reasoning-plus 14B on MacBook Pro M2 Pro 32GB
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: 16.8 tok/s decode · 11.5s TTFT (warm) · 42 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

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well16.8 tok/s6292 ms33K
CodingSRuns well16.8 tok/s11535 ms33K
Agentic CodingSTight fit16.8 tok/s16778 ms33K
ReasoningSRuns well16.8 tok/s13632 ms33K
RAGSTight fit16.8 tok/s20973 ms33K

Quantization options

How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on MacBook Pro M2 Pro 32GB (23.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.7 GB
LowS86
Q3_K_S
3
7.2 GB
LowS87
NVFP4
4
8.2 GB
MediumS88
Q4_K_M
4
9.0 GB
MediumS88
Q5_K_M
5
10.6 GB
HighS89
Q6_K
6
12.1 GB
HighS90
Q8_0Best for your GPU
8
15.7 GB
Very HighS90
F16
16
30.1 GB
MaximumF0

Get started

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

Run

ollama run phi4-reasoning

Your hardware

More models your MacBook Pro M2 Pro 32GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BA19 tok/s
AlibabaQwen 3.5 27B27BS8.5 tok/s
AlibabaQwen 3.6 27B27BS7 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS20.1 tok/s
AlibabaQwen 3.5 35B A3B35BA16.6 tok/s

Frequently asked questions

Can MacBook Pro M2 Pro 32GB run Phi-4-reasoning-plus 14B?

Yes, MacBook Pro M2 Pro 32GB can run Phi-4-reasoning-plus 14B with a S grade (Runs well). Expected decode speed: 16.8 tok/s.

How much VRAM does Phi-4-reasoning-plus 14B need?

Phi-4-reasoning-plus 14B (14.699999809265137B parameters) requires approximately 16.4 GB of memory with Q4_K_M quantization.

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

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

What speed will Phi-4-reasoning-plus 14B run at on MacBook Pro M2 Pro 32GB?

On MacBook Pro M2 Pro 32GB, Phi-4-reasoning-plus 14B achieves approximately 16.8 tokens per second decode speed with a time-to-first-token of 11535ms using Q4_K_M quantization.

Can MacBook Pro M2 Pro 32GB run Phi-4-reasoning-plus 14B for coding?

For coding workloads, Phi-4-reasoning-plus 14B on MacBook Pro M2 Pro 32GB receives a S grade with 16.8 tok/s and 33K context.

What context window can Phi-4-reasoning-plus 14B use on MacBook Pro M2 Pro 32GB?

On MacBook Pro M2 Pro 32GB, Phi-4-reasoning-plus 14B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M2 Pro 32GB as fast as VRAM for Phi-4-reasoning-plus 14B?

Not always. MacBook Pro M2 Pro 32GB 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 M2 Pro 32GBSee all hardware for Phi-4-reasoning-plus 14B
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