Apple M3 Pro for local LLMs
Written by Jakub Rusinowski · Last updated
With 36 GB at 153 GB/s, the M3 Pro runs 113 catalogued models at Q4_K_M with 8K context. The largest that fits is Gemma 3 27B Instruct (~25.4 GB), and the top pick is Qwen 3.6 35B-A3B at 24–51 tok/s.
The 3nm upgrade to M2 Pro. Up to 36 GB unified memory at 153 GB/s. Handles Qwen 3 14B and Phi-4 14B comfortably at Q4. 30W total system power in a laptop.
Models that run on the M3 Pro
Q4_K_M, 8K context, 27 GB usable. Ranked by quality and speed.
| Model | Memory · marker = 27 GB | VRAM | Speed |
|---|---|---|---|
| Qwen 3.6 35B-A3B Qwen 3.6 | 22.1 GB | 24–51 tok/s | |
| Nex-N2.5 mini Nex-N2.5 | 21.9 GB | 14–29 tok/s | |
| Nex-N2 mini Nex-N2 | 21.9 GB | 14–29 tok/s | |
| Qwen 3.5 35B-A3B Qwen 3.5 | 21.9 GB | 14–29 tok/s | |
| Laguna XS 2.1 33B-A3B Poolside Laguna XS 2.1 | 20.7 GB | 14–29 tok/s | |
| Nemotron-Cascade 2 30B-A3B Nemotron Cascade 2 | 19.9 GB | 13–27 tok/s | |
| Qwen 3 30B-A3B (MoE) Qwen 3 | 20 GB | 18–37 tok/s | |
| Qwen3-Coder 30B-A3B (MoE) Qwen3-Coder | 20 GB | 18–37 tok/s | |
| GLM-4.7-Flash 30B-A3B GLM-4.7 / GLM-Z1 | 18.9 GB | 14–29 tok/s | |
| Nemotron 3 Nano Omni 30B-A3B Nemotron 3 Nano Omni | 18.9 GB | 14–29 tok/s | |
| North Mini Code 1.0 30B-A3B North Mini Code | 18.9 GB | 14–29 tok/s | |
| Nemotron 3.5 Lightning 30B-A3B Nemotron 3.5 | 18.9 GB | 14–29 tok/s |
Buy it or rent the same memory
Buy the card, or rent a GPU with the same memory by the hour to try models first.
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Speed vs other GPUs
Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated
Specifications
Specs last updated 2026-09-29.
- Memory
- 36 GB
- Memory bandwidth
- 153 GB/s
- Architecture
- ARM, 3nm TSMC
- Series
- Apple Silicon
- Board power
- 30 W
- Release year
- 2023
- Usable for models
- 27 GB (~75% of unified)
Similar GPUs
Frequently asked questions
Can the Apple M3 Pro run local LLMs?
Yes. With 36 GB (27 GB usable by a model) it runs 113 of the catalogued models at Q4_K_M with 8K context; the largest is Gemma 3 27B Instruct, needing about 25.4 GB.
How fast is the Apple M3 Pro for AI inference?
It is estimated to run Llama 3.1 8B at 9.7–20 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 27 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.
What LLMs can I run on 36 GB?
Among the best that fit: Qwen 3.6 35B-A3B, Nex-N2.5 mini, Nex-N2 mini, Qwen 3.5 35B-A3B, Laguna XS 2.1 33B-A3B. The quickest start is Ollama: ollama run qwen3:14b.
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Can I run it on the M3 Pro?
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