Will It Run AI

Can Phi 3 Medium 14B run on MacBook Pro M3 24GB?

YES — Tight Fit

B57Good
Estimated from fit model

Phi 3 Medium 14B needs ~15.1 GB VRAM. MacBook Pro M3 24GB has 17.3 GB. With Q4_K_M quantization, expect ~9 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: 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) 15.1 GB, 8.6 tok/s, Tight fit
15.1 GB required17.3 GB available
87% VRAM used

Fit status

Tight fit

Decode

8.6 tok/s

TTFT

22618 ms

Safe context

28K

Memory

15.1 GB / 17.3 GB

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime0.9 GB
Headroom2.6 GB

See how fast it feels

See how fast it feelsPhi 3 Medium 14B on MacBook Pro M3 24GB
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: 8.6 tok/s decode · 22.6s TTFT (warm) · 21 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 well8.6 tok/s12337 ms28K
CodingBTight fit8.6 tok/s22618 ms28K
Agentic CodingBRuns with offload (needs ~0.4 GB host RAM)7.8 tok/s36029 ms28K
ReasoningBTight fit8.6 tok/s26730 ms28K
RAGBRuns with offload7.3 tok/s48414 ms28K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on MacBook Pro M3 24GB (17.3 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowB60
Q3_K_S
3
6.9 GB
LowB61
NVFP4
4
7.8 GB
MediumB62
Q4_K_M
4
8.5 GB
MediumB62
Q5_K_M
5
10.1 GB
HighB62
Q6_KBest for your GPU
6
11.5 GB
HighB62
Q8_0
8
15.0 GB
Very HighF0
F16
16
28.7 GB
MaximumF0

Get started

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

Run

ollama run phi3:medium

升级选项

能流畅运行 Phi 3 Medium 14B 的硬件

Frequently asked questions

Can MacBook Pro M3 24GB run Phi 3 Medium 14B?

Yes, MacBook Pro M3 24GB can run Phi 3 Medium 14B with a B grade (Tight fit). Expected decode speed: 8.6 tok/s.

How much VRAM does Phi 3 Medium 14B need?

Phi 3 Medium 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 3 Medium 14B?

The recommended quantization for Phi 3 Medium 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 3 Medium 14B run at on MacBook Pro M3 24GB?

On MacBook Pro M3 24GB, Phi 3 Medium 14B achieves approximately 8.6 tokens per second decode speed with a time-to-first-token of 22618ms using Q4_K_M quantization.

Can MacBook Pro M3 24GB run Phi 3 Medium 14B for coding?

For coding workloads, Phi 3 Medium 14B on MacBook Pro M3 24GB receives a B grade with 8.6 tok/s and 28K context.

What context window can Phi 3 Medium 14B use on MacBook Pro M3 24GB?

On MacBook Pro M3 24GB, Phi 3 Medium 14B can safely use up to 28K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M3 24GB as fast as VRAM for Phi 3 Medium 14B?

Not always. MacBook Pro M3 24GB 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 24GBSee all hardware for Phi 3 Medium 14B
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