Apple M5 Pro for local LLMs
Written by Jakub Rusinowski · Last updated
With 64 GB at 307 GB/s, the M5 Pro runs 126 catalogued models at Q4_K_M with 8K context. The largest that fits is Llama 3.3 70B Instruct (~45.7 GB), and the top pick is K2 Horizon MoVA 36B-A4B at 24–50 tok/s.
Up to 64 GB unified memory at 307 GB/s — double the memory ceiling of the M4 Pro. Released March 2026 in the MacBook Pro 14"/16". Comfortably fits 32B models at Q4.
Models that run on the M5 Pro
Q4_K_M, 8K context, 48 GB usable. Ranked by quality and speed.
| Model | Memory · marker = 48 GB | VRAM | Speed |
|---|---|---|---|
| K2 Horizon MoVA 36B-A4B K2 Horizon | 25 GB | 24–50 tok/s | |
| Qwen 3.6 35B-A3B Qwen 3.6 | 22.2 GB | 43–89 tok/s | |
| Nex-N2.5 mini Nex-N2.5 | 21.9 GB | 26–54 tok/s | |
| Nex-N2 mini Nex-N2 | 21.9 GB | 26–54 tok/s | |
| Qwen 3.5 35B-A3B Qwen 3.5 | 21.9 GB | 26–54 tok/s | |
| Laguna XS 2.1 33B-A3B Poolside Laguna XS 2.1 | 20.7 GB | 26–55 tok/s | |
| Granite 4.0 Small-H 32B-A9B IBM Granite 4.0 | 20.1 GB | 14–29 tok/s | |
| Nemotron-Cascade 2 30B-A3B Nemotron Cascade 2 | 19.9 GB | 25–51 tok/s | |
| Qwen 3 30B-A3B (MoE) Qwen 3 | 20 GB | 33–69 tok/s | |
| Qwen3-Coder 30B-A3B (MoE) Qwen3-Coder | 20 GB | 33–69 tok/s | |
| GLM-4.7-Flash 30B-A3B GLM-4.7 / GLM-Z1 | 18.9 GB | 27–55 tok/s | |
| Nemotron 3 Nano Omni 30B-A3B Nemotron 3 Nano Omni | 18.9 GB | 27–55 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.
or compare on Vast.ai from $0.77/hr (typical low · varies)
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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 2026-07-12.
- Memory
- 64 GB
- Memory bandwidth
- 307 GB/s
- Architecture
- ARM, 3nm TSMC
- Series
- Apple Silicon
- Board power
- 30 W
- Release year
- 2026
- Usable for models
- 48 GB (~75% of unified)
Similar GPUs
Frequently asked questions
Can the Apple M5 Pro run local LLMs?
Yes. With 64 GB (48 GB usable by a model) it runs 126 of the catalogued models at Q4_K_M with 8K context; the largest is Llama 3.3 70B Instruct, needing about 45.7 GB.
How fast is the Apple M5 Pro for AI inference?
It is estimated to run Llama 3.1 8B at 19–39 tok/s at Q4_K_M. Llama 3.3 70B is estimated at 2.5–5.1 tok/s. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.
What LLMs can I run on 64 GB?
Among the best that fit: K2 Horizon MoVA 36B-A4B, Qwen 3.6 35B-A3B, Nex-N2.5 mini, Nex-N2 mini, Qwen 3.5 35B-A3B. The quickest start is Ollama: ollama run qwen3:14b.
Keep going
Can I run it on the M5 Pro?
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