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Mac mini M4 16GB

Apple · M4 · 16GB Unified Memory · Can run 49 models

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Manufacturer Apple
Unified Mem 16 GB
Chip M4
CPU Cores 10
GPU Cores 10
Neural Engine 16
Bandwidth 120 GB/s
MSRP $599
Released Nov 8, 2024

AI Notes

The Mac mini M4 16GB is the most affordable entry point for local AI on Apple Silicon. With 16GB of unified memory, it can run 7B models comfortably and 13B models with Q4 quantization. Its compact form factor and low power consumption make it ideal as a dedicated AI inference server.

Compatible Models

Model Parameters Best Quant VRAM Used Fit Est. Speed
Qwen 3 0.6B 600M Q4_K_M 2.5 GB Runs ~48 tok/s
Gemma 3 1B 1B Q8_0 2 GB Runs ~60 tok/s
Llama 3.2 1B 1B Q8_0 3 GB Runs ~40 tok/s
DeepSeek R1 1.5B 1.5B Q8_0 3 GB Runs ~40 tok/s
Gemma 2 2B 2B Q8_0 4 GB Runs ~30 tok/s
Gemma 3n E2B 2B Q4_K_M 3.3 GB Runs ~36 tok/s
Llama 3.2 3B 3B Q8_0 5 GB Runs ~24 tok/s
Phi-3 Mini 3.8B 3.8B Q8_0 5.8 GB Runs ~21 tok/s
Phi-4 Mini 3.8B 3.8B Q4_K_M 4.5 GB Runs ~27 tok/s
Gemma 3 4B 4B Q4_K_M 5 GB Runs ~24 tok/s
Gemma 3n E4B 4B Q4_K_M 4.5 GB Runs ~27 tok/s
Qwen 3 4B 4B Q4_K_M 4.5 GB Runs ~27 tok/s
DeepSeek R1 7B 7B Q8_0 9 GB Runs ~13 tok/s
Falcon 3 7B 7B Q4_K_M 6.8 GB Runs ~18 tok/s
Mistral 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 Coder 7B 7B Q8_0 9 GB Runs ~13 tok/s
Qwen 2.5 VL 7B 7B Q4_K_M 7 GB Runs ~17 tok/s
Cogito 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
DeepSeek R1 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Llama 3.1 8B 8B Q8_0 10 GB Runs ~12 tok/s
Nemotron 3 Nano 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Qwen 3 8B 8B Q4_K_M 7.5 GB Runs ~16 tok/s
Gemma 2 9B 9B Q8_0 11 GB Runs ~11 tok/s
Falcon 3 10B 10B Q4_K_M 8.5 GB Runs ~14 tok/s
Llama 3.2 Vision 11B 11B Q4_K_M 8.5 GB Runs ~14 tok/s
Gemma 3 12B 12B Q4_K_M 10.5 GB Runs ~11 tok/s
Mistral Nemo 12B 12B Q4_K_M 9.5 GB Runs ~13 tok/s
DeepSeek R1 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Phi-4 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Phi-4 Reasoning 14B 14B Q4_K_M 11 GB Runs ~11 tok/s
Qwen 2.5 14B 14B Q4_K_M 9.9 GB Runs ~12 tok/s
Qwen 2.5 Coder 14B 14B Q4_K_M 12 GB Runs ~10 tok/s
Qwen 3 14B 14B Q4_K_M 12 GB Runs ~10 tok/s
Codestral 22B 22B Q4_K_M 14.7 GB Runs (tight) ~8 tok/s
StarCoder2 15B 15B Q8_0 17 GB CPU Offload ~2 tok/s
Devstral 24B 24B Q4_K_M 17 GB CPU Offload ~2 tok/s
Magistral Small 24B 24B Q4_K_M 17 GB CPU Offload ~2 tok/s
Mistral Small 3.1 24B 24B Q4_K_M 18 GB CPU Offload ~2 tok/s
Gemma 2 27B 27B Q4_K_M 17.7 GB CPU Offload ~2 tok/s
Gemma 3 27B 27B Q4_K_M 20 GB CPU Offload ~2 tok/s
Qwen 3 30B-A3B (MoE) 30B Q4_K_M 22 GB CPU Offload ~2 tok/s
Cogito 32B 32B Q4_K_M 21.5 GB CPU Offload ~2 tok/s
DeepSeek R1 32B 32B Q4_K_M 20.7 GB CPU Offload ~2 tok/s
Qwen 2.5 32B 32B Q4_K_M 20.7 GB CPU Offload ~2 tok/s
Qwen 2.5 Coder 32B 32B Q4_K_M 23 GB CPU Offload ~2 tok/s
Qwen 3 32B 32B Q4_K_M 23 GB CPU Offload ~2 tok/s
QwQ 32B 32B Q4_K_M 21.5 GB CPU Offload ~2 tok/s
Command R 35B 35B Q4_K_M 22.5 GB CPU Offload ~2 tok/s
20 model(s) are too large for this hardware.