Samprix

What AI can a Mac mini (M5 Pro) with 48 GB run?

A Mac mini (M5 Pro) with 48 GB can give a local model 36 GB of memory. At a 4K context, 40 of the 42 models we track fit entirely on it; the largest is Qwen3 32B.

Apple Specs last checked: how
Your computer
Context length
Memory a model can use 36 GB 75% of 48 GB unified memory · source

Models on this machine

  • Model file
  • Context
  • Allowance
  • Your GPU memory

Fits

40
  • Qwen3 32B
    Alibaba · Q8_0
    Needs 34 GB 1.9 GB spare
    Context up to
    11,893
  • Qwen3 32B
    Alibaba · Q4_K_M
    Needs 20 GB 16 GB spare
    Context up to
    40,960
  • Qwen2.5 32B
    Alibaba · Q4_K_M
    Needs 20 GB 16 GB spare
    Context up to
    32,768
  • DeepSeek-R1 Distill 32B
    DeepSeek · Q4_K_M
    Needs 20 GB 16 GB spare
    Context up to
    69,114
  • Qwen2.5 Coder 32B
    Alibaba · Q4_K_M
    Needs 20 GB 16 GB spare
    Context up to
    32,768
  • Qwen3 14B
    Alibaba · Q8_0
    Needs 16 GB 20 GB spare
    Context up to
    40,960
  • Mistral Small 24B
    Mistral AI · Q4_K_M
    Needs 14 GB 22 GB spare
    Context up to
    32,768
  • Mistral Small 22B
    Mistral AI · Q4_K_M
    Needs 13 GB 23 GB spare
    Context up to
    32,768
  • Qwen3 14B
    Alibaba · Q4_K_M
    Needs 9.8 GB 26 GB spare
    Context up to
    40,960
  • Phi-4 14B
    Microsoft · Q4_K_M
    Needs 9.8 GB 26 GB spare
    Context up to
    16,384
  • Qwen2.5 14B
    Alibaba · Q4_K_M
    Needs 9.6 GB 26 GB spare
    Context up to
    32,768
  • DeepSeek-R1 Distill 14B
    DeepSeek · Q4_K_M
    Needs 9.6 GB 26 GB spare
    Context up to
    131,072
  • Qwen2.5 Coder 14B
    Alibaba · Q4_K_M
    Needs 9.6 GB 26 GB spare
    Context up to
    32,768
  • Qwen3 8B
    Alibaba · Q8_0
    Needs 9.4 GB 27 GB spare
    Context up to
    40,960
  • Phi-3 medium 14B
    Microsoft · Q4_K_M
    Needs 9.3 GB 27 GB spare
    Context up to
    131,072
  • OLMo 2 13B
    Allen Institute for AI · Q4_K_M
    Needs 11 GB 25 GB spare
    Context up to
    4,096
  • Mistral Nemo 12B
    Mistral AI · Q4_K_M
    Needs 8.1 GB 28 GB spare
    Context up to
    131,072
  • Qwen3 8B
    Alibaba · Q4_K_M
    Needs 5.9 GB 30 GB spare
    Context up to
    40,960
  • DeepSeek-R1 0528 8B
    DeepSeek · Q4_K_M
    Needs 5.9 GB 30 GB spare
    Context up to
    131,072
  • DeepSeek-R1 Distill 8B
    DeepSeek · Q4_K_M
    Needs 5.6 GB 30 GB spare
    Context up to
    131,072
  • Dolphin 3.0 8B
    Cognitive Computations · Q4_K_M
    Needs 5.6 GB 30 GB spare
    Context up to
    131,072
  • Qwen2.5 7B
    Alibaba · Q4_K_M
    Needs 5.1 GB 31 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 7B
    Alibaba · Q4_K_M
    Needs 5.1 GB 31 GB spare
    Context up to
    32,768
  • DeepSeek-R1 Distill 7B
    DeepSeek · Q4_K_M
    Needs 5.1 GB 31 GB spare
    Context up to
    131,072
  • OLMo 2 7B
    Allen Institute for AI · Q4_K_M
    Needs 6.7 GB 29 GB spare
    Context up to
    4,096
  • Mistral 7B
    Mistral AI · Q4_K_M
    Needs 5.1 GB 31 GB spare
    Context up to
    32,768
  • Qwen3 4B
    Alibaba · Q4_K_M
    Needs 3.5 GB 33 GB spare
    Context up to
    40,960
  • Phi-4 mini 3.8B
    Microsoft · Q4_K_M
    Needs 3.3 GB 33 GB spare
    Context up to
    131,072
  • Phi-3 mini 3.8B
    Microsoft · Q4_K_M
    Needs 4.2 GB 32 GB spare
    Context up to
    4,096
  • Qwen2.5 3B
    Alibaba · Q4_K_M
    Needs 2.4 GB 34 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 3B
    Alibaba · Q4_K_M
    Needs 2.4 GB 34 GB spare
    Context up to
    32,768
  • Qwen3 1.7B
    Alibaba · Q4_K_M
    Needs 2.2 GB 34 GB spare
    Context up to
    40,960
  • DeepSeek-R1 Distill 1.5B
    DeepSeek · Q4_K_M
    Needs 1.6 GB 34 GB spare
    Context up to
    131,072
  • SmolLM2 1.7B
    Hugging Face · Q4_K_M
    Needs 2.3 GB 34 GB spare
    Context up to
    8,192
  • Qwen2.5 1.5B
    Alibaba · Q4_K_M
    Needs 1.5 GB 34 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 1.5B
    Alibaba · Q4_K_M
    Needs 1.5 GB 34 GB spare
    Context up to
    32,768
  • TinyLlama 1.1B
    TinyLlama · Q4_K_M
    Needs 1.2 GB 35 GB spare
    Context up to
    2,048
  • Qwen3 0.6B
    Alibaba · Q4_K_M
    Needs 1.4 GB 35 GB spare
    Context up to
    40,960
  • Qwen2.5 0.5B
    Alibaba · Q4_K_M
    Needs 0.9 GB 35 GB spare
    Context up to
    32,768
  • SmolLM2 360M
    Hugging Face · Q4_K_M
    Needs 0.9 GB 35 GB spare
    Context up to
    8,192

Won’t fit

2
Memory needed = model file + context + a 0.5 GB allowance (our estimate). See methodology.

Frequently asked questions

What’s the biggest AI model a Mac mini (M5 Pro) with 48 GB can run?

Qwen3 32B (Q8_0, a 35 GB download) is the largest of the 42 models we track that fits entirely in the 36 GB a Mac mini (M5 Pro) with 48 GB can give a model at a 4K context, with 1.9 GB to spare and room for up to 11,893 tokens of context.

Can a Mac mini (M5 Pro) with 48 GB run DeepSeek-R1 Distill 70B?

Not entirely in its own memory. DeepSeek-R1 Distill 70B (Q4_K_M) needs 42 GB at a 4K context, and a Mac mini (M5 Pro) with 48 GB can give a model 36 GB. A Mac has no separate memory to spill into, so you need a version with more memory or a smaller download of the model.

How much memory can a Mac mini (M5 Pro) with 48 GB give an AI model?

About 36 GB: 75% of its 48 GB of unified memory, because macOS and your other apps share the same memory. The 48 GB is from Mac mini tech specs (checked Oct 2, 2026); the 75% is our estimate.

How fast will local AI run on a Mac mini (M5 Pro) with 48 GB?

Hardware makers and model publishers don’t publish tokens-per-second figures, so there is no source we could cite. We only show whether a model fits and how much context it leaves room for.

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