Can Qwen 3 8B run on Mac mini M2 24GB?

YES — Runs Great

S89Excellent

Estimated from fit model

Qwen 3 8B needs ~10.6 GB VRAM. Mac mini M2 24GB has 17.3 GB. With Q4_K_M quantization, expect ~14 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) — 10.6 GB, 14.3 tok/s, Runs well

10.6 GB required17.3 GB available

61% VRAM used

Fit status

Runs well

Decode

14.3 tok/s

TTFT

13521 ms

Safe context

65K

Memory

10.6 GB / 17.3 GB

Memory breakdown

Weights4.9 GB

KV Cache2.2 GB

Runtime0.9 GB

Headroom2.6 GB

See how fast it feels

See how fast it feelsQwen 3 8B on Mac mini M2 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: 14.3 tok/s decode · 13.5s TTFT (warm) · 36 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	14.3 tok/s	7375 ms	65K
Coding	S	Runs well	14.3 tok/s	13521 ms	65K
Agentic Coding	S	Runs well	14.3 tok/s	19667 ms	65K
Reasoning	S	Runs well	14.3 tok/s	15979 ms	65K
RAG	S	Runs well	14.3 tok/s	24583 ms	65K

Quantization options

How Qwen 3 8B (8B params) fits at each quantization level on Mac mini M2 24GB (17.3 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	S86
Q3_K_S	3	3.9 GB	Low	S87
NVFP4	4	4.5 GB	Medium	S88
Q4_K_M	4	4.9 GB	Medium	S88
Q5_K_M	5	5.8 GB	High	S89
Q6_K	6	6.6 GB	High	S89
Q8_0Best for your GPU	8	8.6 GB	Very High	S91
F16	16	16.4 GB	Maximum	F0

Get started

Copy-paste commands to run Qwen 3 8B on your machine.

Run

ollama run qwen3:8b

Your hardware

More models your Mac mini M2 24GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	12.7 tok/s
Magistral Small 2507	24B	B	3.7 tok/s
Devstral Small 2 24B Instruct	24B	B	3.7 tok/s
Qwen 3 14B	14B	S	8.2 tok/s

Frequently asked questions

Can Mac mini M2 24GB run Qwen 3 8B?

Yes, Mac mini M2 24GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 14.3 tok/s.

How much VRAM does Qwen 3 8B need?

Qwen 3 8B (8B parameters) requires approximately 10.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3 8B?

The recommended quantization for Qwen 3 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3 8B run at on Mac mini M2 24GB?

On Mac mini M2 24GB, Qwen 3 8B achieves approximately 14.3 tokens per second decode speed with a time-to-first-token of 13521ms using Q4_K_M quantization.

Can Mac mini M2 24GB run Qwen 3 8B for coding?

For coding workloads, Qwen 3 8B on Mac mini M2 24GB receives a S grade with 14.3 tok/s and 65K context.

What context window can Qwen 3 8B use on Mac mini M2 24GB?

On Mac mini M2 24GB, Qwen 3 8B can safely use up to 65K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

Is unified memory on Mac mini M2 24GB as fast as VRAM for Qwen 3 8B?

Not always. Mac mini M2 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 Mac mini M2 24GB See all hardware for Qwen 3 8B

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