VOOZH about

URL: https://willitrunai.com/can-run/phi-3-medium-14b-on-m2-max-32gb


Can Phi 3 Medium 14B run on MacBook Pro M2 Max 32GB?

YES — Runs Great

B64Good
Estimated from fit model

Phi 3 Medium 14B needs ~15.9 GB VRAM. MacBook Pro M2 Max 32GB has 23.0 GB. With Q4_K_M quantization, expect ~29 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Balanced
Share:

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) — 15.9 GB, 29.2 tok/s, Runs well
15.9 GB required23.0 GB available
69% VRAM used

Fit status

Runs well

Decode

29.2 tok/s

TTFT

6629 ms

Safe context

53K

Memory

15.9 GB / 23.0 GB

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime0.9 GB
Headroom3.5 GB

See how fast it feels

See how fast it feelsPhi 3 Medium 14B on MacBook Pro M2 Max 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: 29.2 tok/s decode · 6.6s TTFT (warm) · 73 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
ChatBRuns well29.2 tok/s3616 ms53K
CodingBRuns well29.2 tok/s6629 ms53K
Agentic CodingBTight fit27.2 tok/s10366 ms53K
ReasoningBRuns well29.2 tok/s7835 ms53K
RAGBTight fit29.2 tok/s12053 ms53K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on MacBook Pro M2 Max 32GB (23.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowB57
Q3_K_S
3
6.9 GB
LowB58
NVFP4
4

Get started

Copy-paste commands to run Phi 3 Medium 14B on your machine.

Run

ollama run phi3:medium

Upgrade options

Hardware that runs Phi 3 Medium 14B well

RX 7900 XTX 24GBBudget pick
960 GB/s (+560)
B
Raises estimated decode speed by about 198%.87 tok/s decode

Raises estimated decode speed by about 198%.

~$999 MSRP

👁 NVIDIA
RTX 3090 24GBBest value
936 GB/s (+536)
B
Raises estimated decode speed by about 177%.80.8 tok/s decode

Raises estimated decode speed by about 177%.

~$1,499 MSRP

Frequently asked questions

See all results for MacBook Pro M2 Max 32GBSee all hardware for Phi 3 Medium 14B
7.8 GB
Medium
B59
Q4_K_M
4
8.5 GB
MediumB59
Q5_K_M
5
10.1 GB
HighB60
Q6_K
6
11.5 GB
HighB61
Q8_0Best for your GPU
8
15.0 GB
Very HighB61
F16
16
28.7 GB
MaximumF0

Not always. MacBook Pro M2 Max 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.