Will It Run AI

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

YES — Runs Great

A84Great
Estimated from fit model

Phi-4 Mini Reasoning 4B needs ~8.6 GB VRAM. MacBook Pro M3 Pro 36GB has 25.9 GB. With Q4_K_M quantization, expect ~51 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) — 8.6 GB, 50.8 tok/s, Runs well
8.6 GB required25.9 GB available
33% VRAM used

Fit status

Runs well

Decode

50.8 tok/s

TTFT

3812 ms

Safe context

131K

Memory

8.6 GB / 25.9 GB

Memory breakdown

Weights2.3 GB
KV Cache1.5 GB
Runtime0.9 GB
Headroom3.9 GB

See how fast it feels

See how fast it feelsPhi-4 Mini Reasoning 4B 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: 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
ChatARuns well50.8 tok/s2079 ms131K
CodingARuns well50.8 tok/s3812 ms131K
Agentic CodingSRuns well50.8 tok/s5545 ms131K
ReasoningARuns well50.8 tok/s4506 ms131K
RAGSRuns well50.8 tok/s6932 ms131K

Quantization options

How Phi-4 Mini Reasoning 4B (3.799999952316284B params) fits at each quantization level on MacBook Pro M3 Pro 36GB (25.9 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
1.5 GB
LowA81
Q3_K_S
3
1.9 GB
LowA81
NVFP4
4
2.1 GB
MediumA81
Q4_K_M
4
2.3 GB
MediumA81
Q5_K_M
5
2.7 GB
HighA81
Q6_K
6
3.1 GB
HighA81
Q8_0
8
4.1 GB
Very HighA82
F16Best for your GPU
16
7.8 GB
MaximumA84

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 36GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen3-Coder 30B A3B Instruct30.5BS16.6 tok/s
AlibabaQwen 3.5 27B27BS7.2 tok/s
AlibabaQwen 3.6 27B27BS5.5 tok/s
AlibabaQwen 3.6 35B A3B35BA12.1 tok/s
AlibabaQwen3-VL 30B A3B Instruct30BS17.1 tok/s

Frequently asked questions

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

Yes, MacBook Pro M3 Pro 36GB can run Phi-4 Mini Reasoning 4B with a A grade (Runs well). Expected decode speed: 50.8 tok/s.

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

Phi-4 Mini Reasoning 4B (3.799999952316284B parameters) requires approximately 8.6 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 36GB?

On MacBook Pro M3 Pro 36GB, Phi-4 Mini Reasoning 4B achieves approximately 50.8 tokens per second decode speed with a time-to-first-token of 3812ms using Q4_K_M quantization.

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

For coding workloads, Phi-4 Mini Reasoning 4B on MacBook Pro M3 Pro 36GB receives a A grade with 50.8 tok/s and 131K context.

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

On MacBook Pro M3 Pro 36GB, Phi-4 Mini Reasoning 4B can safely use up to 131K 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 36GB as fast as VRAM for Phi-4 Mini Reasoning 4B?

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 36GBSee all hardware for Phi-4 Mini Reasoning 4B
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