MacBook Pro M5 Max 36GB

Apple · M5 Max · 36GB Unified Memory · Can run 91 models

Manufacturer	Apple
Unified Mem	36 GB
Chip	M5 Max
CPU Cores	16
GPU Cores	32
Neural Engine	16
Bandwidth	410 GB/s
MSRP	$3,199
Released	Mar 11, 2026

AI Notes

The MacBook Pro M5 Max 36GB is a powerhouse for local AI inference. With 410 GB/s memory bandwidth and 32 GPU cores, it delivers exceptionally fast token generation. The 36GB of unified memory fits 30B models comfortably and can handle 70B models with aggressive quantization.

Compatible Models

Model	Parameters	Best Quant	VRAM Used	Fit	Est. Speed
Qwen 3 0.6B	600M	Q4_K_M	2.5 GB	Runs	~164 tok/s
Qwen 3.5 0.8B	800M	Q4_K_M	1.5 GB	Runs	~273 tok/s
Gemma 3 1B	1B	Q8_0	2 GB	Runs	~205 tok/s
Llama 3.2 1B	1B	Q8_0	3 GB	Runs	~137 tok/s
DeepSeek R1 1.5B	1.5B	Q8_0	3 GB	Runs	~137 tok/s
SmolLM2 1.7B	1.7B	Q8_0	2.7 GB	Runs	~152 tok/s
Gemma 2 2B	2B	Q8_0	4 GB	Runs	~103 tok/s
Gemma 3n E2B	2B	Q4_K_M	3.3 GB	Runs	~124 tok/s
Gemma 4 E2B	2B	Q4_K_M	4 GB	Runs	~103 tok/s
Qwen 3.5 2B	2B	Q4_K_M	3 GB	Runs	~137 tok/s
Llama 3.2 3B	3B	Q8_0	5 GB	Runs	~82 tok/s
StarCoder2 3B	3B	Q4_K_M	3.5 GB	Runs	~117 tok/s
Phi-3 Mini 3.8B	3.8B	Q8_0	5.8 GB	Runs	~71 tok/s
Phi-4 Mini 3.8B	3.8B	Q4_K_M	4.5 GB	Runs	~91 tok/s
Gemma 3 4B	4B	Q4_K_M	5 GB	Runs	~82 tok/s
Gemma 3n E4B	4B	Q4_K_M	4.5 GB	Runs	~91 tok/s
Gemma 4 E4B	4B	Q4_K_M	6 GB	Runs	~68 tok/s
Qwen 3 4B	4B	Q4_K_M	4.5 GB	Runs	~91 tok/s
Qwen 3.5 4B	4B	Q4_K_M	4.5 GB	Runs	~91 tok/s
Yi 1.5 6B	6B	Q4_K_M	5 GB	Runs	~82 tok/s
Codestral Mamba 7B	7B	Q4_K_M	6.9 GB	Runs	~59 tok/s
DeepSeek R1 7B	7B	Q8_0	9 GB	Runs	~46 tok/s
Falcon 3 7B	7B	Q4_K_M	6.8 GB	Runs	~60 tok/s
InternLM 2.5 7B	7B	Q4_K_M	5.5 GB	Runs	~75 tok/s
Mistral 7B	7B	Q8_0	9 GB	Runs	~46 tok/s
OpenChat 3.5 7B	7B	Q4_K_M	6.9 GB	Runs	~59 tok/s
Qwen 2.5 7B	7B	Q8_0	9 GB	Runs	~46 tok/s
Qwen 2.5 Coder 7B	7B	Q8_0	9 GB	Runs	~46 tok/s
Qwen 2.5 VL 7B	7B	Q4_K_M	7 GB	Runs	~59 tok/s
StarCoder2 7B	7B	Q4_K_M	5.5 GB	Runs	~75 tok/s
WizardLM 2 7B	7B	Q4_K_M	6.9 GB	Runs	~59 tok/s
Aya Expanse 8B	8B	Q4_K_M	6.5 GB	Runs	~63 tok/s
Cogito 8B	8B	Q4_K_M	7.5 GB	Runs	~55 tok/s
DeepSeek R1 8B	8B	Q4_K_M	7.5 GB	Runs	~55 tok/s
Dolphin 3 8B	8B	Q4_K_M	6 GB	Runs	~68 tok/s
Granite 3.3 8B	8B	Q8_0	10 GB	Runs	~41 tok/s
Llama 3.1 8B	8B	Q8_0	10 GB	Runs	~41 tok/s
Nemotron 3 Nano 8B	8B	Q4_K_M	7.5 GB	Runs	~55 tok/s
Nous Hermes 2 8B	8B	Q4_K_M	6 GB	Runs	~68 tok/s
Qwen 3 8B	8B	Q4_K_M	7.5 GB	Runs	~55 tok/s
Gemma 2 9B	9B	Q8_0	11 GB	Runs	~37 tok/s
Qwen 3.5 9B	9B	Q4_K_M	7.5 GB	Runs	~55 tok/s
Yi 1.5 9B	9B	Q4_K_M	6.5 GB	Runs	~63 tok/s
Yi Coder 9B	9B	Q4_K_M	8 GB	Runs	~51 tok/s
Falcon 3 10B	10B	Q4_K_M	8.5 GB	Runs	~48 tok/s
Llama 3.2 Vision 11B	11B	Q4_K_M	8.5 GB	Runs	~48 tok/s
Gemma 3 12B	12B	Q4_K_M	10.5 GB	Runs	~39 tok/s
Mistral Nemo 12B	12B	Q4_K_M	9.5 GB	Runs	~43 tok/s
DeepSeek R1 14B	14B	Q4_K_M	9.9 GB	Runs	~41 tok/s
Phi-4 14B	14B	Q4_K_M	9.9 GB	Runs	~41 tok/s
Phi-4 Reasoning 14B	14B	Q4_K_M	11 GB	Runs	~37 tok/s
Qwen 2.5 14B	14B	Q4_K_M	9.9 GB	Runs	~41 tok/s
Qwen 2.5 Coder 14B	14B	Q4_K_M	12 GB	Runs	~34 tok/s
Qwen 3 14B	14B	Q4_K_M	12 GB	Runs	~34 tok/s
StarCoder2 15B	15B	Q8_0	17 GB	Runs	~24 tok/s
InternLM 2.5 20B	20B	Q4_K_M	12 GB	Runs	~34 tok/s
gpt-oss 20B	21B	MXFP4	15 GB	Runs	~27 tok/s
Codestral 22B	22B	Q4_K_M	14.7 GB	Runs	~28 tok/s
Devstral 24B	24B	Q4_K_M	17 GB	Runs	~24 tok/s
Magistral Small 24B	24B	Q4_K_M	17 GB	Runs	~24 tok/s
Mistral Small 3.1 24B	24B	Q4_K_M	18 GB	Runs	~23 tok/s
Gemma 4 26B	26B	Q4_K_M	20 GB	Runs	~21 tok/s
Gemma 2 27B	27B	Q4_K_M	17.7 GB	Runs	~23 tok/s
Gemma 3 27B	27B	Q4_K_M	20 GB	Runs	~21 tok/s
Qwen 3.5 27B	27B	Q4_K_M	19 GB	Runs	~22 tok/s
Qwen 3.6 27B	27B	Q4_K_M	20 GB	Runs	~21 tok/s
Qwen 3 30B-A3B (MoE)	30B	Q4_K_M	22 GB	Runs	~19 tok/s
Gemma 4 31B	31B	Q4_K_M	22 GB	Runs	~19 tok/s
Aya Expanse 32B	32B	Q4_K_M	22 GB	Runs	~19 tok/s
Cogito 32B	32B	Q4_K_M	21.5 GB	Runs	~19 tok/s
DeepSeek R1 32B	32B	Q4_K_M	20.7 GB	Runs	~20 tok/s
Qwen 2.5 32B	32B	Q4_K_M	20.7 GB	Runs	~20 tok/s
Qwen 2.5 Coder 32B	32B	Q4_K_M	23 GB	Runs	~18 tok/s
Qwen 3 32B	32B	Q4_K_M	23 GB	Runs	~18 tok/s
QwQ 32B	32B	Q4_K_M	21.5 GB	Runs	~19 tok/s
Laguna XS 2.1	33B	Q4_K_M	22 GB	Runs	~19 tok/s
WizardCoder 33B	33B	Q4_K_M	22 GB	Runs	~19 tok/s
Nous Hermes 2 34B	34B	Q4_K_M	19 GB	Runs	~22 tok/s
Yi 1.5 34B	34B	Q4_K_M	21 GB	Runs	~20 tok/s
Command R 35B	35B	Q4_K_M	22.5 GB	Runs	~18 tok/s
Qwen 3.5 35B A3B	35B	Q4_K_M	12 GB	Runs	~34 tok/s
Qwen 3.6 35B-A3B	35B	Q4_K_M	27 GB	Runs	~15 tok/s
Dolphin Mixtral 8x7B	47B	Q4_K_M	26 GB	Runs	~16 tok/s
Mixtral 8x7B	47B	Q4_K_M	29.7 GB	Runs	~14 tok/s
Cogito 70B	70B	Q4_K_M	43 GB	CPU Offload	~3 tok/s
DeepSeek R1 70B	70B	Q4_K_M	43.5 GB	CPU Offload	~3 tok/s
Llama 3.1 70B	70B	Q4_K_M	43.5 GB	CPU Offload	~3 tok/s
Llama 3.3 70B	70B	Q4_K_M	43.5 GB	CPU Offload	~3 tok/s
Qwen 2.5 72B	72B	Q4_K_M	44.7 GB	CPU Offload	~3 tok/s
Qwen 2.5 VL 72B	72B	Q4_K_M	41 GB	CPU Offload	~3 tok/s
Llama 3.2 Vision 90B	90B	Q4_K_M	50 GB	CPU Offload	~2 tok/s

23 model(s) are too large for this hardware.