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Apple M2 Pro

16GB unified memory  ·  Apple Silicon (Metal/MLX)

Quick answer: The fastest listed local LLM on Apple M2 Pro is llama3.2-3b at 82 tok/s decode, with 9 Q4_K_M models marked as fitting this hardware.
⚠️ Apple Silicon uses unified memory shared between CPU and GPU. macOS typically reserves 3–4GB for system use — effective available memory is ~12GB, not the full 16GB spec. Models near the top of the VRAM limit may OOM on a loaded system.
ℹ️ VRAM estimates assume GGUF format and 2048-token context. Running at 8k+ context adds 2–4GB. Tokens/sec = generation (decode) speed only. 7 rows currently link to community benchmark sources.
Model Quant VRAM Tok/s Data Fits
llama3.2-3b Q4_K_M 2GB 82 Community benchmark ✓
gemma3-4b Q4_K_M 3GB 75 Community benchmark ✓
mistral-7b Q4_K_M 4.7GB 52 Community benchmark ✓
qwen2.5-7b Q4_K_M 4.7GB 50 Community benchmark ✓
llama3.1-8b Q4_K_M 5GB 48 Community benchmark ✓
deepseek-r1-7b Q4_K_M 4.7GB 46 estimate ✓
gemma3-12b Q4_K_M 7.5GB 30 Community benchmark ✓
qwen2.5-14b Q4_K_M 9GB 22 Community benchmark ✓
phi-4-14b Q4_K_M 9GB 20 estimate ✓
gemma3-27b Q4_K_M 16.5GB — estimate ✗ No
llama3.1-70b Q4_K_M 42GB — estimate ✗ No
mistral-24b Q4_K_M 14.4GB — estimate ✗ No
nemotron-51b Q4_K_M 30.6GB — estimate ✗ No
qwen2.5-32b Q4_K_M 19.5GB — estimate ✗ No
qwen2.5-72b Q4_K_M 43.5GB — estimate ✗ No
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Apple M2 Pro local LLM FAQ

What LLMs can run on Apple M2 Pro?

9 Q4_K_M models in this dataset are marked as fitting on Apple M2 Pro. Start with the table rows marked as fitting, then compare VRAM and decode tok/s.

What is the fastest local LLM on Apple M2 Pro?

llama3.2-3b is the fastest listed model on Apple M2 Pro at 82 decode tokens per second.

How much VRAM does Apple M2 Pro have for local LLMs?

Apple M2 Pro has 16GB unified memory, but macOS can reserve several GB, so the practical model budget is closer to 12GB on a loaded system.

Can Apple M2 Pro run 70B local LLMs?

Apple M2 Pro is not marked as fitting the listed 70B-class Q4_K_M models in this dataset. Check the fit column before trying larger context windows.

What quantization should I use on Apple M2 Pro?

Use Q4_K_M as the baseline for this site. It is the comparison format used across the current benchmark table and keeps VRAM requirements predictable.

Last updated: 2026-06-11 · Source · Improve this data