Can Phi-4 14B run on MacBook Air M3 24GB?

YES — Tight Fit

A78Great

Estimated from fit model

Phi-4 14B needs ~15.1 GB VRAM. MacBook Air M3 24GB has 17.3 GB. With Q4_K_M quantization, expect ~9 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth

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

16K

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-4 14B on MacBook Air 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	8.6 tok/s	12337 ms	16K
Coding	A	Tight fit	8.6 tok/s	22618 ms	16K
Agentic Coding	A	Runs with offload (needs ~0.4 GB host RAM)	7.8 tok/s	36029 ms	16K
Reasoning	A	Tight fit	8.6 tok/s	26730 ms	16K
RAG	A	Runs with offload (needs ~0.4 GB host RAM)	7.8 tok/s	45036 ms

Quantization options

How Phi-4 14B (14B params) fits at each quantization level on MacBook Air M3 24GB (17.3 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	A80
Q3_K_S	3	6.9 GB	Low	A81
NVFP4	4

Get started

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

Run

ollama run phi4

Your hardware

More models your MacBook Air M3 24GB can run

Model	Params	Grade	Decode	Capabilities
Magistral Small 2507	24B	B	3.8 tok/s
Devstral Small 2 24B Instruct	24B	B	3.8 tok/s

Frequently asked questions

Can MacBook Air M3 24GB run Phi-4 14B?

Yes, MacBook Air M3 24GB can run Phi-4 14B with a A grade (Tight fit). Expected decode speed: 8.6 tok/s.

How much VRAM does Phi-4 14B need?

Phi-4 14B (14B parameters) requires approximately 15.1 GB of memory with Q4_K_M quantization.

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

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

What speed will Phi-4 14B run at on MacBook Air M3 24GB?

On MacBook Air M3 24GB, Phi-4 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 Air M3 24GB run Phi-4 14B for coding?

For coding workloads, Phi-4 14B on MacBook Air M3 24GB receives a A grade with 8.6 tok/s and 16K context.

What context window can Phi-4 14B use on MacBook Air M3 24GB?

On MacBook Air M3 24GB, Phi-4 14B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.

Is unified memory on MacBook Air M3 24GB as fast as VRAM for Phi-4 14B?

Not always. MacBook Air 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 Air M3 24GB See all hardware for Phi-4 14B

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