Samprix

What AI can a Mac mini (M6) with 24 GB run?

A Mac mini (M6) with 24 GB can give a local model 18 GB of memory. At a 4K context, 35 of the 42 models we track fit entirely on it; the largest is Qwen3 14B.

Apple Specs last checked: how
Your computer
Context length
Memory a model can use 18 GB 75% of 24 GB unified memory · source

Models on this machine

  • Model file
  • Context
  • Allowance
  • Your GPU memory

Fits

35
  • Qwen3 14B
    Alibaba · Q8_0
    Needs 16 GB 2 GB spare
    Context up to
    17,031
  • Mistral Small 24B
    Mistral AI · Q4_K_M
    Needs 14 GB 3.8 GB spare
    Context up to
    29,238
  • Mistral Small 22B
    Mistral AI · Q4_K_M
    Needs 13 GB 4.5 GB spare
    Context up to
    25,244
  • Qwen3 14B
    Alibaba · Q4_K_M
    Needs 9.8 GB 8.2 GB spare
    Context up to
    40,960
  • Phi-4 14B
    Microsoft · Q4_K_M
    Needs 9.8 GB 8.2 GB spare
    Context up to
    16,384
  • Qwen2.5 14B
    Alibaba · Q4_K_M
    Needs 9.6 GB 8.4 GB spare
    Context up to
    32,768
  • DeepSeek-R1 Distill 14B
    DeepSeek · Q4_K_M
    Needs 9.6 GB 8.4 GB spare
    Context up to
    49,796
  • Qwen2.5 Coder 14B
    Alibaba · Q4_K_M
    Needs 9.6 GB 8.4 GB spare
    Context up to
    32,768
  • Qwen3 8B
    Alibaba · Q8_0
    Needs 9.4 GB 8.6 GB spare
    Context up to
    40,960
  • Phi-3 medium 14B
    Microsoft · Q4_K_M
    Needs 9.3 GB 8.7 GB spare
    Context up to
    49,758
  • OLMo 2 13B
    Allen Institute for AI · Q4_K_M
    Needs 11 GB 6.6 GB spare
    Context up to
    4,096
  • Mistral Nemo 12B
    Mistral AI · Q4_K_M
    Needs 8.1 GB 9.9 GB spare
    Context up to
    68,911
  • Qwen3 8B
    Alibaba · Q4_K_M
    Needs 5.9 GB 12 GB spare
    Context up to
    40,960
  • DeepSeek-R1 0528 8B
    DeepSeek · Q4_K_M
    Needs 5.9 GB 12 GB spare
    Context up to
    92,166
  • DeepSeek-R1 Distill 8B
    DeepSeek · Q4_K_M
    Needs 5.6 GB 12 GB spare
    Context up to
    105,975
  • Dolphin 3.0 8B
    Cognitive Computations · Q4_K_M
    Needs 5.6 GB 12 GB spare
    Context up to
    105,975
  • Qwen2.5 7B
    Alibaba · Q4_K_M
    Needs 5.1 GB 13 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 7B
    Alibaba · Q4_K_M
    Needs 5.1 GB 13 GB spare
    Context up to
    32,768
  • DeepSeek-R1 Distill 7B
    DeepSeek · Q4_K_M
    Needs 5.1 GB 13 GB spare
    Context up to
    131,072
  • OLMo 2 7B
    Allen Institute for AI · Q4_K_M
    Needs 6.7 GB 11 GB spare
    Context up to
    4,096
  • Mistral 7B
    Mistral AI · Q4_K_M
    Needs 5.1 GB 13 GB spare
    Context up to
    32,768
  • Qwen3 4B
    Alibaba · Q4_K_M
    Needs 3.5 GB 15 GB spare
    Context up to
    40,960
  • Phi-4 mini 3.8B
    Microsoft · Q4_K_M
    Needs 3.3 GB 15 GB spare
    Context up to
    124,286
  • Phi-3 mini 3.8B
    Microsoft · Q4_K_M
    Needs 4.2 GB 14 GB spare
    Context up to
    4,096
  • Qwen2.5 3B
    Alibaba · Q4_K_M
    Needs 2.4 GB 16 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 3B
    Alibaba · Q4_K_M
    Needs 2.4 GB 16 GB spare
    Context up to
    32,768
  • Qwen3 1.7B
    Alibaba · Q4_K_M
    Needs 2.2 GB 16 GB spare
    Context up to
    40,960
  • DeepSeek-R1 Distill 1.5B
    DeepSeek · Q4_K_M
    Needs 1.6 GB 16 GB spare
    Context up to
    131,072
  • SmolLM2 1.7B
    Hugging Face · Q4_K_M
    Needs 2.3 GB 16 GB spare
    Context up to
    8,192
  • Qwen2.5 1.5B
    Alibaba · Q4_K_M
    Needs 1.5 GB 16 GB spare
    Context up to
    32,768
  • Qwen2.5 Coder 1.5B
    Alibaba · Q4_K_M
    Needs 1.5 GB 16 GB spare
    Context up to
    32,768
  • TinyLlama 1.1B
    TinyLlama · Q4_K_M
    Needs 1.2 GB 17 GB spare
    Context up to
    2,048
  • Qwen3 0.6B
    Alibaba · Q4_K_M
    Needs 1.4 GB 17 GB spare
    Context up to
    40,960
  • Qwen2.5 0.5B
    Alibaba · Q4_K_M
    Needs 0.9 GB 17 GB spare
    Context up to
    32,768
  • SmolLM2 360M
    Hugging Face · Q4_K_M
    Needs 0.9 GB 17 GB spare
    Context up to
    8,192

Won’t fit

7
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 (M6) with 24 GB can run?

Qwen3 14B (Q8_0, a 16 GB download) is the largest of the 42 models we track that fits entirely in the 18 GB a Mac mini (M6) with 24 GB can give a model at a 4K context, with 2 GB to spare and room for up to 17,031 tokens of context.

Can a Mac mini (M6) with 24 GB run Qwen3 32B?

Not entirely in its own memory. Qwen3 32B (Q4_K_M) needs 20 GB at a 4K context, and a Mac mini (M6) with 24 GB can give a model 18 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 (M6) with 24 GB give an AI model?

About 18 GB: 75% of its 24 GB of unified memory, because macOS and your other apps share the same memory. The 24 GB is from Mac mini tech specs (checked Oct 2, 2026); the 75% is our estimate.

Which other graphics cards or Macs run the same models?

MacBook Air (M5), 24 GB and Mac mini (M5 Pro), 24 GB have the same 24 GB of unified memory, so the same models fit. How fast they run differs, but makers don’t publish speed figures we could cite.

How fast will local AI run on a Mac mini (M6) with 24 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.

Other graphics cards and Macs

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