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

YES — Tight Fit

S87Excellent

Estimated from fit model

Qwen 3 14B needs ~14.5 GB VRAM. MacBook Pro M3 24GB has 17.3 GB. With Q4_K_M quantization, expect ~8 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) — 14.5 GB, 8.6 tok/s, Tight fit

14.5 GB required17.3 GB available

84% VRAM used

Fit status

Tight fit

Decode

8.6 tok/s

TTFT

22513 ms

Safe context

34K

Memory

14.5 GB / 17.3 GB

Memory breakdown

Weights8.5 GB

KV Cache2.4 GB

Runtime0.9 GB

Headroom2.6 GB

See how fast it feels

See how fast it feelsQwen 3 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 · 22.5s TTFT (warm) · 22 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	S	Runs well	8.6 tok/s	12280 ms	34K
Coding	S	Tight fit	8.0 tok/s	24314 ms	34K
Agentic Coding	S	Runs with offload	8.6 tok/s	32746 ms	34K
Reasoning	S	Tight fit	8.0 tok/s	28735 ms	34K
RAG	S	Runs with offload	8.6 tok/s	40932 ms	34K

Quantization options

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

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	S89
Q3_K_S	3	6.9 GB	Low	S91
NVFP4	4	7.8 GB	Medium	S91
Q4_K_M	4	8.5 GB	Medium	S92
Q5_K_M	5	10.1 GB	High	S92
Q6_KBest for your GPU	6	11.5 GB	High	S91
Q8_0	8	15.0 GB	Very High	F0
F16	16	28.7 GB	Maximum	F0

Get started

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

Run

ollama run qwen3

Your hardware

More models your MacBook Pro 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 Pro M3 24GB run Qwen 3 14B?

Yes, MacBook Pro M3 24GB can run Qwen 3 14B with a S grade (Tight fit). Expected decode speed: 8.0 tok/s.

How much VRAM does Qwen 3 14B need?

Qwen 3 14B (14B parameters) requires approximately 14.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 14B?

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

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

On MacBook Pro M3 24GB, Qwen 3 14B achieves approximately 8.0 tokens per second decode speed with a time-to-first-token of 24314ms using Q4_K_M quantization.

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

For coding workloads, Qwen 3 14B on MacBook Pro M3 24GB receives a S grade with 8.0 tok/s and 34K context.

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

On MacBook Pro M3 24GB, Qwen 3 14B can safely use up to 34K 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 24GB as fast as VRAM for Qwen 3 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 24GB See all hardware for Qwen 3 14B

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