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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Qwen3-VL 30B A3B Instruct/on Mac mini M2 24GB

Can it run?

Can Mac mini M2 24GB run Qwen3-VL 30B A3B Instruct?

FWon't run

Too heavy

Using Q4_K_M in vLLM

Capabilities:

Fit status

Too heavy

Decode

9.3 tok/s

TTFT

20712 ms

Safe context

11K

Memory

24.1 GB / 17.3 GB

Memory breakdown

Weights18.3 GB
KV Cache0.8 GB
Runtime2.4 GB
Headroom2.6 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingFToo heavy9.3 tok/s30127 ms23K
ChatFToo heavy9.3 tok/s11298 ms6K
CodingFToo heavy9.3 tok/s20712 ms11K
RAGFToo heavy9.3 tok/s37659 ms23K
ReasoningFToo heavy9.3 tok/s24478 ms11K

Quantization options

How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on Mac mini M2 24GB (17.3 GB usable).

QuantBitsVRAMQualityFit
Q2_KBest for your GPU
2
11.7 GB
LowC44
Q3_K_S
3
14.7 GB
LowC45
NVFP4
4
16.8 GB
MediumC45
Q4_K_M
4
18.3 GB
MediumF0
Q5_K_M
5
21.6 GB
HighF0
Q6_K
6
24.6 GB
HighF0
Q8_0
8
32.1 GB
Very HighF0
F16
16
61.5 GB
MaximumF0

Upgrade options

Hardware that runs Qwen3-VL 30B A3B Instruct well

AMDRX 7900 XTX 24GBBest value
C99.4 tok/s decode

~$999 MSRP

AppleMac mini M4 64GBBudget pick
C12.4 tok/s decode

~$1,099 MSRP

AppleMacBook Pro M4 Max 48GBApple upgrade
B49.5 tok/s decode

~$2,499 MSRP

AMDAMD Instinct MI100 32GBBiggest leap
B114.8 tok/s decode

 

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