What can MacBook Pro 16" M4 Max run for coding?

Build: MacBook Pro M4 Max 64GB

Memory: 64 GB unified memory
Runner: MLX-LM (Apple Metal)

Runs comfortably
204 models

Ranked by fit for coding use case + predicted speed. Click a row for VRAM breakdown.

#1CodeGemma 7B
7B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 8.4 GBHeadroom: 47.6 GB
ollama run codegemma:7b
71
tok/s
Estimated
Weights
4.20 GB
KV cache
3.50 GB
Activations
0.22 GB
Runtime
0.50 GB
#2DeepSeek Coder V2 Lite (16B)
16B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 18.5 GBHeadroom: 37.5 GB
ollama run deepseek-coder-v2:16b
31
tok/s
Estimated
Weights
9.50 GB
KV cache
8.00 GB
Activations
0.48 GB
Runtime
0.50 GB
#3Qwen 2.5 7B Instruct
7B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 9.5 GBHeadroom: 46.5 GB
ollama run qwen2.5:7b
40
tok/s
Estimated
Weights
8.10 GB
KV cache
0.47 GB
Activations
0.41 GB
Runtime
0.50 GB
#4Codestral 22B
22B
mistral
Quant: Q8_0Context: 8,192VRAM: 35.7 GBHeadroom: 20.3 GB
ollama run codestral:22b
13
tok/s
Estimated
Weights
23.00 GB
KV cache
11.00 GB
Activations
1.16 GB
Runtime
0.50 GB
#5Qwen 3 8B
8B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 13.1 GBHeadroom: 42.9 GB
ollama run qwen3:8b
35
tok/s
Estimated
Weights
8.20 GB
KV cache
4.00 GB
Activations
0.42 GB
Runtime
0.50 GB
#6Qwen 3 14B
14B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 23.3 GBHeadroom: 32.7 GB
ollama run qwen3:14b
20
tok/s
Estimated
Weights
15.00 GB
KV cache
7.00 GB
Activations
0.76 GB
Runtime
0.50 GB
#7Qwen 2.5 14B Instruct
14B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 24.0 GBHeadroom: 32.0 GB
ollama run qwen2.5:14b
20
tok/s
Estimated
Weights
15.70 GB
KV cache
7.00 GB
Activations
0.79 GB
Runtime
0.50 GB
#8Qwen 2.5 Coder 32B Instruct
32B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 38.4 GBHeadroom: 17.6 GB
ollama run qwen2.5-coder:32b
9
tok/s
Estimated
Weights
34.00 GB
KV cache
2.15 GB
Activations
1.71 GB
Runtime
0.50 GB
#9Qwen 3 30B-A3B
30B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 49.1 GBHeadroom: 6.9 GB
ollama run qwen3:30b
9
tok/s
Estimated
Weights
32.00 GB
KV cache
15.00 GB
Activations
1.61 GB
Runtime
0.50 GB
#10Muse Glimmer 30B
30B
other
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 34.8 GBHeadroom: 21.2 GB
ollama run muse-glimmer
9
tok/s
Estimated
Weights
32.00 GB
KV cache
0.71 GB
Activations
1.61 GB
Runtime
0.50 GB
#11Gemma 4 31B Dense
31B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 50.7 GBHeadroom: 5.3 GB
ollama run gemma4:31b
9
tok/s
Estimated
Weights
33.00 GB
KV cache
15.50 GB
Activations
1.66 GB
Runtime
0.50 GB
#12StarCoder 2 3B
3B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 4.1 GBHeadroom: 51.9 GB
166
tok/s
Estimated
Weights
2.00 GB
KV cache
1.50 GB
Activations
0.11 GB
Runtime
0.50 GB

Runs with tradeoffs
11 models

Tight VRAM, partial CPU offload, or context-limited.

Qwen 3 32B
32B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 52.2 GBHeadroom: 3.8 GB
  • Tight VRAM fit — only 3.8 GB headroom left for context growth
ollama run qwen3:32b
9
tok/s
Estimated
Weights
34.00 GB
KV cache
16.00 GB
Activations
1.71 GB
Runtime
0.50 GB
Qwen 2.5 32B Instruct
32B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 52.2 GBHeadroom: 3.8 GB
  • Tight VRAM fit — only 3.8 GB headroom left for context growth
ollama run qwen2.5:32b
9
tok/s
Estimated
Weights
34.00 GB
KV cache
16.00 GB
Activations
1.71 GB
Runtime
0.50 GB
Llama 3.3 70B Instruct
70B
llama
Commercial OK
Quant: Q5_K_MContext: 8,192VRAM: 52.5 GBHeadroom: 3.5 GB
  • Tight VRAM fit — only 3.5 GB headroom left for context growth
ollama run llama3.3:70b
6
tok/s
Estimated
Weights
47.00 GB
KV cache
2.68 GB
Activations
2.36 GB
Runtime
0.50 GB
Mixtral 8x7B Instruct
47B
mixtral
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 53.4 GBHeadroom: 2.6 GB
  • Tight VRAM fit — only 2.6 GB headroom left for context growth
ollama run mixtral:8x7b
11
tok/s
Estimated
Weights
28.00 GB
KV cache
23.50 GB
Activations
1.41 GB
Runtime
0.50 GB
DeepSeek R1 Distill Qwen 32B
32B
deepseek
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 52.2 GBHeadroom: 3.8 GB
  • Tight VRAM fit — only 3.8 GB headroom left for context growth
ollama run deepseek-r1:32b
9
tok/s
Estimated
Weights
34.00 GB
KV cache
16.00 GB
Activations
1.71 GB
Runtime
0.50 GB
OpenBioLLM Llama 3 70B
70B
openbiollm
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 53.4 GBHeadroom: 2.6 GB
  • Tight VRAM fit — only 2.6 GB headroom left for context growth
7
tok/s
Estimated
Weights
42.00 GB
KV cache
8.75 GB
Activations
2.10 GB
Runtime
0.50 GB
Qwen 2.5 72B Instruct
72B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 52.6 GBHeadroom: 3.4 GB
  • Tight VRAM fit — only 3.4 GB headroom left for context growth
ollama run qwen2.5:72b
7
tok/s
Estimated
Weights
41.00 GB
KV cache
9.00 GB
Activations
2.05 GB
Runtime
0.50 GB
Molmo 72B
72B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 52.6 GBHeadroom: 3.4 GB
  • Tight VRAM fit — only 3.4 GB headroom left for context growth
7
tok/s
Estimated
Weights
41.00 GB
KV cache
9.00 GB
Activations
2.05 GB
Runtime
0.50 GB

What if you upgraded?

Hypothetical scenarios. We re-ran the compatibility engine for each.

Move up an Apple memory tier

~$200–400 over base

On Apple Silicon, more unified memory is the only path forward — VRAM and system RAM are the same pool.

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Won't run
top 5 popular models

Need more memory than you have. Shown for orientation.

DeepSeek V4 Pro (1.6T MoE)
1600B
deepseek
Commercial OK

Needs ~1024 GB unified memory minimum at smallest quant; you have 56 GB available after OS overhead.

Qwen 3.5 235B-A17B (MoE)
397B
qwen
Commercial OK

Needs ~256 GB unified memory minimum at smallest quant; you have 56 GB available after OS overhead.

Qwen 3 235B-A22B
235B
qwen
Commercial OK

Needs ~160 GB unified memory minimum at smallest quant; you have 56 GB available after OS overhead.

DeepSeek R1 (671B reasoning)
671B
deepseek
Commercial OK

Needs ~420 GB unified memory minimum at smallest quant; you have 56 GB available after OS overhead.

Llama 4 Scout
109B
llama
Commercial OK

Needs ~80 GB unified memory minimum at smallest quant; you have 56 GB available after OS overhead.

How to read these numbers

Measured here
Measured here - RunLocalAI ran this exact combo on owner hardware with public evidence.

Source-backed
Source-backed / community - a reproduced public source supports the speed, but it is not labeled as owner-measured.

Extrapolated
Extrapolated - predicted from a measured benchmark on similar-bandwidth hardware.

Estimated
Estimated - formula based on VRAM bandwidth and model architecture; not a benchmark row.

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