GPU GUIDE · APPLE
Best AI models for the
Apple M2 Pro (16GB)
The Apple M2 Pro (16GB) has 16.0GB of unified memory. Below are the top 30 open-source AI models that fit, ranked by composite benchmark score. Each row shows the best quantization that fits your hardware.
VRAM
16.0GB
Brand
apple
Models that fit
30
Generation
M2
Top 30 models for the Apple M2 Pro (16GB)
01
54.0Qwen 3.5 9B
9.0BBest fit: Q8_0 · 10.6GBCan I run it? →
02
45.1Qwen 3.5 4B
4.0BBest fit: fp16 · 9.0GBCan I run it? →
03
40.8GPT-OSS 20B
20.0BBest fit: Q5_K_M · 15.2GBCan I run it? →
04
36.7Devstral 2
24.0BBest fit: Q4_K_M · 15.6GBCan I run it? →
05
32.4Devstral Small 2 24B Instruct 2512
24.0BBest fit: Q4_1 · 16.0GBCan I run it? →
06
31.7Devstral Small 2
7.0BBest fit: fp16 · 15.0GBCan I run it? →
07
31.3gemma 4 E4B it
8.0BBest fit: Q8_0 · 9.5GBCan I run it? →
08
30.3Qwen3 4B Thinking 2507
4.0BBest fit: fp16 · 9.0GBCan I run it? →
09
27.8Qwen3 VL 8B Thinking
8.8BBest fit: Q8_0 · 10.3GBCan I run it? →
10
27.4DeepSeek R1 0528 Qwen3 8B
8.2BBest fit: Q8_0 · 9.7GBCan I run it? →
11
27.2Qwen 3.5 2B
2.0BBest fit: fp16 · 5.0GBCan I run it? →
12
27.0Qwen3 14B
14.8BBest fit: Q6_K · 13.2GBCan I run it? →
13
26.7Ministral 3 14B
14.0BBest fit: Q8_0 · 15.9GBCan I run it? →
14
26.6Ministral 3 14B 2512
13.9BBest fit: Q8_0 · 15.8GBCan I run it? →
15
26.4DeepSeek R1 Distill Qwen 14B
14.8BBest fit: Q6_K · 13.2GBCan I run it? →
16
25.4gemma 4 E2B it
5.1BBest fit: fp16 · 11.2GBCan I run it? →
17
25.0Ministral 3 8B
8.0BBest fit: Q8_0 · 9.5GBCan I run it? →
18
25.0Gemma 4 E2B
2.0BBest fit: fp16 · 5.0GBCan I run it? →
19
25.1Mistral Small 3.2 24B
24.0BBest fit: Q4_1 · 16.0GBCan I run it? →
20
24.8Nemotron Nano 12B 2 VL (free)
13.2BBest fit: Q8_0 · 15.0GBCan I run it? →
21
24.7Ministral 3 8B 2512
8.9BBest fit: Q8_0 · 10.5GBCan I run it? →
22
24.6Nemotron Nano 9B V2 (free)
8.9BBest fit: Q8_0 · 10.5GBCan I run it? →
23
24.5NVIDIA Nemotron 3 Nano 4B BF16
4.0BBest fit: Q8_0 · 5.3GBCan I run it? →
24
23.8Qwen3 VL 8B Instruct
8.8BBest fit: Q8_0 · 10.3GBCan I run it? →
25
23.7Qwen3 4B
4.0BBest fit: Q8_0 · 5.3GBCan I run it? →
26
22.9Qwen3 VL 4B Thinking
4.4BBest fit: fp16 · 9.8GBCan I run it? →
27
22.0Qwen3 8B
8.2BBest fit: Q8_0 · 9.7GBCan I run it? →
28
21.5Qwen3 4B Instruct 2507
4.0BBest fit: fp16 · 9.0GBCan I run it? →
29
21.1Mistral Small 3
23.6BBest fit: Q4_1 · 15.8GBCan I run it? →
30
20.6Granite 4.1 8B
8.8BBest fit: Q8_0 · 10.3GBCan I run it? →
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FAQ — running AI on the Apple M2 Pro (16GB)
How many AI models can the Apple M2 Pro (16GB) run?
With 16.0GB of unified memory, the Apple M2 Pro (16GB) can run 30+ open-source models from our database, including Qwen 3.5 9B, Qwen 3.5 4B, GPT-OSS 20B.
What's the largest LLM I can run on a Apple M2 Pro (16GB)?
The biggest model that fits is approximately 24.0B. Larger models would need to be quantized further or won't fit at all.
Is 16.0GB of unified memory enough for local AI?
Yes for most use cases — 16.0GB runs 7B-13B class models at high quality. For 30B+ models you'll need to use heavy quantization or upgrade.