Skip to content

Mac mini M4 16GB

Apple · M4 · 16GB Unified Memory · Can run 81 models

BuyAppleAmazon
ManufacturerApple
Unified Mem16 GB
ChipM4
CPU Cores10
GPU Cores10
Neural Engine16
Bandwidth120 GB/s
MSRP$599
ReleasedNov 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

ModelParametersBest QuantVRAM UsedFitEst. Speed
Qwen 3 0.6B600MQ4_K_M2.5 GBRuns~48 tok/s
Qwen 3.5 0.8B800MQ4_K_M1.5 GBRuns~80 tok/s
Gemma 3 1B1BQ8_02 GBRuns~60 tok/s
Llama 3.2 1B1BQ8_03 GBRuns~40 tok/s
DeepSeek R1 1.5B1.5BQ8_03 GBRuns~40 tok/s
SmolLM2 1.7B1.7BQ8_02.7 GBRuns~44 tok/s
Gemma 2 2B2BQ8_04 GBRuns~30 tok/s
Gemma 3n E2B2BQ4_K_M3.3 GBRuns~36 tok/s
Gemma 4 E2B2BQ4_K_M4 GBRuns~30 tok/s
Qwen 3.5 2B2BQ4_K_M3 GBRuns~40 tok/s
Llama 3.2 3B3BQ8_05 GBRuns~24 tok/s
StarCoder2 3B3BQ4_K_M3.5 GBRuns~34 tok/s
Phi-3 Mini 3.8B3.8BQ8_05.8 GBRuns~21 tok/s
Phi-4 Mini 3.8B3.8BQ4_K_M4.5 GBRuns~27 tok/s
Gemma 3 4B4BQ4_K_M5 GBRuns~24 tok/s
Gemma 3n E4B4BQ4_K_M4.5 GBRuns~27 tok/s
Gemma 4 E4B4BQ4_K_M6 GBRuns~20 tok/s
Qwen 3 4B4BQ4_K_M4.5 GBRuns~27 tok/s
Qwen 3.5 4B4BQ4_K_M4.5 GBRuns~27 tok/s
Yi 1.5 6B6BQ4_K_M5 GBRuns~24 tok/s
Codestral Mamba 7B7BQ4_K_M6.9 GBRuns~17 tok/s
DeepSeek R1 7B7BQ8_09 GBRuns~13 tok/s
Falcon 3 7B7BQ4_K_M6.8 GBRuns~18 tok/s
InternLM 2.5 7B7BQ4_K_M5.5 GBRuns~22 tok/s
Mistral 7B7BQ8_09 GBRuns~13 tok/s
OpenChat 3.5 7B7BQ4_K_M6.9 GBRuns~17 tok/s
Qwen 2.5 7B7BQ8_09 GBRuns~13 tok/s
Qwen 2.5 Coder 7B7BQ8_09 GBRuns~13 tok/s
Qwen 2.5 VL 7B7BQ4_K_M7 GBRuns~17 tok/s
StarCoder2 7B7BQ4_K_M5.5 GBRuns~22 tok/s
WizardLM 2 7B7BQ4_K_M6.9 GBRuns~17 tok/s
Aya Expanse 8B8BQ4_K_M6.5 GBRuns~18 tok/s
Cogito 8B8BQ4_K_M7.5 GBRuns~16 tok/s
DeepSeek R1 8B8BQ4_K_M7.5 GBRuns~16 tok/s
Dolphin 3 8B8BQ4_K_M6 GBRuns~20 tok/s
Granite 3.3 8B8BQ8_010 GBRuns~12 tok/s
Llama 3.1 8B8BQ8_010 GBRuns~12 tok/s
Nemotron 3 Nano 8B8BQ4_K_M7.5 GBRuns~16 tok/s
Nous Hermes 2 8B8BQ4_K_M6 GBRuns~20 tok/s
Qwen 3 8B8BQ4_K_M7.5 GBRuns~16 tok/s
Gemma 2 9B9BQ8_011 GBRuns~11 tok/s
Qwen 3.5 9B9BQ4_K_M7.5 GBRuns~16 tok/s
Yi 1.5 9B9BQ4_K_M6.5 GBRuns~18 tok/s
Yi Coder 9B9BQ4_K_M8 GBRuns~15 tok/s
Falcon 3 10B10BQ4_K_M8.5 GBRuns~14 tok/s
Llama 3.2 Vision 11B11BQ4_K_M8.5 GBRuns~14 tok/s
Gemma 3 12B12BQ4_K_M10.5 GBRuns~11 tok/s
Mistral Nemo 12B12BQ4_K_M9.5 GBRuns~13 tok/s
DeepSeek R1 14B14BQ4_K_M9.9 GBRuns~12 tok/s
Phi-4 14B14BQ4_K_M9.9 GBRuns~12 tok/s
Phi-4 Reasoning 14B14BQ4_K_M11 GBRuns~11 tok/s
Qwen 2.5 14B14BQ4_K_M9.9 GBRuns~12 tok/s
Qwen 2.5 Coder 14B14BQ4_K_M12 GBRuns~10 tok/s
Qwen 3 14B14BQ4_K_M12 GBRuns~10 tok/s
InternLM 2.5 20B20BQ4_K_M12 GBRuns~10 tok/s
Qwen 3.5 35B A3B35BQ4_K_M12 GBRuns~10 tok/s
gpt-oss 20B21BMXFP415 GBRuns (tight)~8 tok/s
Codestral 22B22BQ4_K_M14.7 GBRuns (tight)~8 tok/s
StarCoder2 15B15BQ8_017 GBCPU Offload~2 tok/s
Devstral 24B24BQ4_K_M17 GBCPU Offload~2 tok/s
Magistral Small 24B24BQ4_K_M17 GBCPU Offload~2 tok/s
Mistral Small 3.1 24B24BQ4_K_M18 GBCPU Offload~2 tok/s
Gemma 4 26B26BQ4_K_M20 GBCPU Offload~2 tok/s
Gemma 2 27B27BQ4_K_M17.7 GBCPU Offload~2 tok/s
Gemma 3 27B27BQ4_K_M20 GBCPU Offload~2 tok/s
Qwen 3.5 27B27BQ4_K_M19 GBCPU Offload~2 tok/s
Qwen 3.6 27B27BQ4_K_M20 GBCPU Offload~2 tok/s
Qwen 3 30B-A3B (MoE)30BQ4_K_M22 GBCPU Offload~2 tok/s
Gemma 4 31B31BQ4_K_M22 GBCPU Offload~2 tok/s
Aya Expanse 32B32BQ4_K_M22 GBCPU Offload~2 tok/s
Cogito 32B32BQ4_K_M21.5 GBCPU Offload~2 tok/s
DeepSeek R1 32B32BQ4_K_M20.7 GBCPU Offload~2 tok/s
Qwen 2.5 32B32BQ4_K_M20.7 GBCPU Offload~2 tok/s
Qwen 2.5 Coder 32B32BQ4_K_M23 GBCPU Offload~2 tok/s
Qwen 3 32B32BQ4_K_M23 GBCPU Offload~2 tok/s
QwQ 32B32BQ4_K_M21.5 GBCPU Offload~2 tok/s
Laguna XS 2.133BQ4_K_M22 GBCPU Offload~2 tok/s
WizardCoder 33B33BQ4_K_M22 GBCPU Offload~2 tok/s
Nous Hermes 2 34B34BQ4_K_M19 GBCPU Offload~2 tok/s
Yi 1.5 34B34BQ4_K_M21 GBCPU Offload~2 tok/s
Command R 35B35BQ4_K_M22.5 GBCPU Offload~2 tok/s
33 model(s) are too large for this hardware.