Will It Run AI

Can Phi-4 Mini Reasoning 4B run on MacBook Pro M3 Pro 18GB?

YES — Runs Great

S88Excellent
Estimated from fit model

Phi-4 Mini Reasoning 4B needs ~6.6 GB VRAM. MacBook Pro M3 Pro 18GB has 13.0 GB. With Q4_K_M quantization, expect ~47 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) — 6.6 GB, 50.8 tok/s, Runs well
6.6 GB required13.0 GB available
51% VRAM used

Fit status

Runs well

Decode

50.8 tok/s

TTFT

3812 ms

Safe context

85K

Memory

6.6 GB / 13.0 GB

Memory breakdown

Weights2.3 GB
KV Cache1.5 GB
Runtime0.9 GB
Headroom1.9 GB

See how fast it feels

See how fast it feelsPhi-4 Mini Reasoning 4B on MacBook Pro M3 Pro 18GB
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: 50.8 tok/s decode · 3.8s TTFT (warm) · 127 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 well47.2 tok/s2235 ms85K
CodingSRuns well47.2 tok/s4098 ms85K
Agentic CodingSRuns well47.2 tok/s5961 ms85K
ReasoningSRuns well47.2 tok/s4843 ms85K
RAGSRuns well47.2 tok/s7451 ms85K

Quantization options

How Phi-4 Mini Reasoning 4B (3.799999952316284B params) fits at each quantization level on MacBook Pro M3 Pro 18GB (13.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
1.5 GB
LowA84
Q3_K_S
3
1.9 GB
LowA85
NVFP4
4
2.1 GB
MediumA85
Q4_K_M
4
2.3 GB
MediumA85
Q5_K_M
5
2.7 GB
HighS85
Q6_K
6
3.1 GB
HighS86
Q8_0
8
4.1 GB
Very HighS87
F16Best for your GPU
16
7.8 GB
MaximumS89

Get started

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

Run

ollama run phi4-mini

Your hardware

More models your MacBook Pro M3 Pro 18GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3.5 9B9BS21.4 tok/s
AlibabaQwen 3 14B14BA12.3 tok/s
AlibabaQwen 3.5 4B4BS48.2 tok/s
AlibabaQwen 3 8B8BS24.1 tok/s
MicrosoftPhi-4-reasoning-plus 14B14.7BA10.6 tok/s

Frequently asked questions

Can MacBook Pro M3 Pro 18GB run Phi-4 Mini Reasoning 4B?

Yes, MacBook Pro M3 Pro 18GB can run Phi-4 Mini Reasoning 4B with a S grade (Runs well). Expected decode speed: 47.2 tok/s.

How much VRAM does Phi-4 Mini Reasoning 4B need?

Phi-4 Mini Reasoning 4B (3.799999952316284B parameters) requires approximately 6.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi-4 Mini Reasoning 4B?

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

What speed will Phi-4 Mini Reasoning 4B run at on MacBook Pro M3 Pro 18GB?

On MacBook Pro M3 Pro 18GB, Phi-4 Mini Reasoning 4B achieves approximately 47.2 tokens per second decode speed with a time-to-first-token of 4098ms using Q4_K_M quantization.

Can MacBook Pro M3 Pro 18GB run Phi-4 Mini Reasoning 4B for coding?

For coding workloads, Phi-4 Mini Reasoning 4B on MacBook Pro M3 Pro 18GB receives a S grade with 47.2 tok/s and 85K context.

What context window can Phi-4 Mini Reasoning 4B use on MacBook Pro M3 Pro 18GB?

On MacBook Pro M3 Pro 18GB, Phi-4 Mini Reasoning 4B can safely use up to 85K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M3 Pro 18GB as fast as VRAM for Phi-4 Mini Reasoning 4B?

Not always. MacBook Pro M3 Pro 18GB 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 18GBSee all hardware for Phi-4 Mini Reasoning 4B
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