← Every GPUApple · 18 or 36 GB unified memory · 150 GB/s

What can the Apple M3 Pro run?

With 18 GB, 4 of 12 popular open models fit. The best pick is Qwen3 4B at about 33 tok/s, faster than you can read.

ollama run qwen3:4b

First time? Install Ollama, then paste that into a terminal. Is this your machine? Check it on the homepage.

18 GB unified memory · about 12 GB for models

Every model the Apple M3 Pro 18 GB can run

4 of 12 fit. Best pick: Qwen3 4B.

  • Qwen3 4BQuick everyday chat and summaries
    ~33 tok/s
    Runs greatqwen3:4b
  • Qwen3 8BA solid all-rounder for chat and writing
    ~16 tok/s
    Usableqwen3:8b
  • Gemma 3 12BReads images as well as text
    ~10 tok/s
    Usablegemma3:12b
  • Qwen3 14BNoticeably smarter at reasoning and code
    ~9 tok/s
    Slowqwen3:14b
  • gpt-oss 20BOpenAI's open model. Fast, strong reasoning
    needs 16 GB
    Too biggpt-oss:20b
  • Gemma 3 27BGoogle's best open model for its size
    needs 19 GB
    Too biggemma3:27b
  • Qwen3 30B-A3B30B smarts at small-model speed
    needs 21 GB
    Too bigqwen3:30b
  • Qwen3 32BStrong coding and long answers
    needs 22 GB
    Too bigqwen3:32b
  • Llama 3.3 70BClose to the big cloud models
    needs 45 GB
    Too bigllama3.3:70b
  • gpt-oss 120BOpenAI's largest open model
    needs 67 GB
    Too biggpt-oss:120b
  • Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigs
    needs 144 GB
    Too bigqwen3:235b
  • DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigs
    needs 406 GB
    Too bigdeepseek-r1:671b
36 GB unified memory · about 24 GB for models

Every model the Apple M3 Pro 36 GB can run

8 of 12 fit. Best pick: Qwen3 30B-A3B.

  • Qwen3 4BQuick everyday chat and summaries
    ~33 tok/s
    Runs greatqwen3:4b
  • Qwen3 8BA solid all-rounder for chat and writing
    ~16 tok/s
    Usableqwen3:8b
  • Gemma 3 12BReads images as well as text
    ~10 tok/s
    Usablegemma3:12b
  • Qwen3 14BNoticeably smarter at reasoning and code
    ~9 tok/s
    Slowqwen3:14b
  • gpt-oss 20BOpenAI's open model. Fast, strong reasoning
    ~26 tok/s
    Usablegpt-oss:20b
  • Gemma 3 27BGoogle's best open model for its size
    ~5 tok/s
    Slowgemma3:27b
  • Qwen3 30B-A3B30B smarts at small-model speed
    ~26 tok/s
    Usableqwen3:30b
  • Qwen3 32BStrong coding and long answers
    ~4 tok/s
    Slowqwen3:32b
  • Llama 3.3 70BClose to the big cloud models
    needs 45 GB
    Too bigllama3.3:70b
  • gpt-oss 120BOpenAI's largest open model
    needs 67 GB
    Too biggpt-oss:120b
  • Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigs
    needs 144 GB
    Too bigqwen3:235b
  • DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigs
    needs 406 GB
    Too bigdeepseek-r1:671b
Common questions

Can the Apple M3 Pro run it?

Can the Apple M3 Pro run Qwen3 30B-A3B?

Yes, with 36 GB or more. Qwen3 30B-A3B needs about 21 GB and the Apple M3 Pro with 36 GB of unified memory leaves about 24 GB for models. Expect about 26 tok/s, about reading speed. The 18 GB version doesn't have room.

Can the Apple M3 Pro run Qwen3 32B?

Yes, with 36 GB or more. Qwen3 32B needs about 22 GB and the Apple M3 Pro with 36 GB of unified memory leaves about 24 GB for models. Expect about 4 tok/s, slow, but it works. The 18 GB version doesn't have room.

Can the Apple M3 Pro run Llama 3.3 70B?

No. Llama 3.3 70B needs about 45 GB and the Apple M3 Pro has at most 36 GB of unified memory, of which about 24 GB is usable for models. The most capable model it runs well is Qwen3 30B-A3B, at about 26 tok/s.

How we estimate

Generating a token reads the model's active weights from memory once, so speed is roughly memory bandwidth (150 GB/s) divided by the active weight size, with efficiency calibrated on our own rack. Sizes are Ollama's default 4-bit downloads plus about 1.2 GB for context. macOS lets the GPU use about two thirds to three quarters of unified memory, so that is what we count. Real results are usually within about a third. Measured one yourself? Send us the number.

Want something bigger?

The Used workstation + 2× Tesla P100 runs Qwen3 32B at about 20 tok/s, from $750 used.

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