Can Qwen 3 4B run on MacBook Air M2 16GB?

YES — Runs Great

A83Great

Estimated from fit model

Qwen 3 4B needs ~7.3 GB VRAM. MacBook Air M2 16GB has 11.5 GB. With Q4_K_M quantization, expect ~29 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: 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) — 7.3 GB, 28.6 tok/s, Runs well

7.3 GB required11.5 GB available

63% VRAM used

Fit status

Runs well

Decode

28.6 tok/s

TTFT

6760 ms

Safe context

33K

Memory

7.3 GB / 11.5 GB

Memory breakdown

Weights2.4 GB

KV Cache2.2 GB

Runtime0.9 GB

Headroom1.7 GB

See how fast it feels

See how fast it feelsQwen 3 4B on MacBook Air M2 16GB
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: 28.6 tok/s decode · 6.8s TTFT (warm) · 72 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	28.6 tok/s	3687 ms	33K
Coding	A	Runs well	28.6 tok/s	6760 ms	33K
Agentic Coding	A	Tight fit	26.6 tok/s	10571 ms	33K
Reasoning	A	Runs well	28.6 tok/s	7990 ms	33K
RAG	A	Tight fit	28.6 tok/s	12292 ms	33K

Quantization options

How Qwen 3 4B (4B params) fits at each quantization level on MacBook Air M2 16GB (11.5 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.6 GB	Low	A79
Q3_K_S	3	2.0 GB	Low	A80
NVFP4	4

Get started

Copy-paste commands to run Qwen 3 4B on your machine.

Run

ollama run qwen3:4b

Your hardware

More models your MacBook Air M2 16GB can run

Model	Params	Grade	Decode	Capabilities
Qwen 3.5 9B	9B	S	12.7 tok/s
Qwen 3 14B	14B	A	6.4 tok/s

Frequently asked questions

Can MacBook Air M2 16GB run Qwen 3 4B?

Yes, MacBook Air M2 16GB can run Qwen 3 4B with a A grade (Runs well). Expected decode speed: 28.6 tok/s.

How much VRAM does Qwen 3 4B need?

Qwen 3 4B (4B parameters) requires approximately 7.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 4B?

The recommended quantization for Qwen 3 4B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 4B run at on MacBook Air M2 16GB?

On MacBook Air M2 16GB, Qwen 3 4B achieves approximately 28.6 tokens per second decode speed with a time-to-first-token of 6760ms using Q4_K_M quantization.

Can MacBook Air M2 16GB run Qwen 3 4B for coding?

For coding workloads, Qwen 3 4B on MacBook Air M2 16GB receives a A grade with 28.6 tok/s and 33K context.

What context window can Qwen 3 4B use on MacBook Air M2 16GB?

On MacBook Air M2 16GB, Qwen 3 4B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

Is unified memory on MacBook Air M2 16GB as fast as VRAM for Qwen 3 4B?

Not always. MacBook Air M2 16GB 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 M2 16GB See all hardware for Qwen 3 4B

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