What can the Apple M5 Pro run?
With 24 GB, 5 of 12 popular open models fit. The best pick is gpt-oss 20B at about 54 tok/s, faster than you can read.
ollama run gpt-oss:20bFirst time? Install Ollama, then paste that into a terminal. Is this your machine? Check it on the homepage.
Every model the Apple M5 Pro 24 GB can run
5 of 12 fit. Best pick: gpt-oss 20B.
- Qwen3 4BQuick everyday chat and summaries~68 tok/sRuns great
qwen3:4b - Qwen3 8BA solid all-rounder for chat and writing~32 tok/sRuns great
qwen3:8b - Gemma 3 12BReads images as well as text~21 tok/sUsable
gemma3:12b - Qwen3 14BNoticeably smarter at reasoning and code~18 tok/sUsable
qwen3:14b - gpt-oss 20BOpenAI's open model. Fast, strong reasoning~54 tok/sRuns great
gpt-oss:20b - Gemma 3 27BGoogle's best open model for its sizeneeds 19 GBToo big
gemma3:27b - Qwen3 30B-A3B30B smarts at small-model speedneeds 21 GBToo big
qwen3:30b - Qwen3 32BStrong coding and long answersneeds 22 GBToo big
qwen3:32b - Llama 3.3 70BClose to the big cloud modelsneeds 45 GBToo big
llama3.3:70b - gpt-oss 120BOpenAI's largest open modelneeds 67 GBToo big
gpt-oss:120b - Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigsneeds 144 GBToo big
qwen3:235b - DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigsneeds 406 GBToo big
deepseek-r1:671b
Every model the Apple M5 Pro 48 GB can run
8 of 12 fit. Best pick: Qwen3 30B-A3B.
- Qwen3 4BQuick everyday chat and summaries~68 tok/sRuns great
qwen3:4b - Qwen3 8BA solid all-rounder for chat and writing~32 tok/sRuns great
qwen3:8b - Gemma 3 12BReads images as well as text~21 tok/sUsable
gemma3:12b - Qwen3 14BNoticeably smarter at reasoning and code~18 tok/sUsable
qwen3:14b - gpt-oss 20BOpenAI's open model. Fast, strong reasoning~54 tok/sRuns great
gpt-oss:20b - Gemma 3 27BGoogle's best open model for its size~10 tok/sSlow
gemma3:27b - Qwen3 30B-A3B30B smarts at small-model speed~54 tok/sRuns great
qwen3:30b - Qwen3 32BStrong coding and long answers~8 tok/sSlow
qwen3:32b - Llama 3.3 70BClose to the big cloud modelsneeds 45 GBToo big
llama3.3:70b - gpt-oss 120BOpenAI's largest open modelneeds 67 GBToo big
gpt-oss:120b - Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigsneeds 144 GBToo big
qwen3:235b - DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigsneeds 406 GBToo big
deepseek-r1:671b
Every model the Apple M5 Pro 64 GB can run
9 of 12 fit. Best pick: Qwen3 30B-A3B.
- Qwen3 4BQuick everyday chat and summaries~68 tok/sRuns great
qwen3:4b - Qwen3 8BA solid all-rounder for chat and writing~32 tok/sRuns great
qwen3:8b - Gemma 3 12BReads images as well as text~21 tok/sUsable
gemma3:12b - Qwen3 14BNoticeably smarter at reasoning and code~18 tok/sUsable
qwen3:14b - gpt-oss 20BOpenAI's open model. Fast, strong reasoning~54 tok/sRuns great
gpt-oss:20b - Gemma 3 27BGoogle's best open model for its size~10 tok/sSlow
gemma3:27b - Qwen3 30B-A3B30B smarts at small-model speed~54 tok/sRuns great
qwen3:30b - Qwen3 32BStrong coding and long answers~8 tok/sSlow
qwen3:32b - Llama 3.3 70BClose to the big cloud models~4 tok/sSlow
llama3.3:70b - gpt-oss 120BOpenAI's largest open modelneeds 67 GBToo big
gpt-oss:120b - Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigsneeds 144 GBToo big
qwen3:235b - DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigsneeds 406 GBToo big
deepseek-r1:671b
Can the Apple M5 Pro run it?
Can the Apple M5 Pro run Qwen3 32B?
Yes, with 48 GB or more. Qwen3 32B needs about 22 GB and the Apple M5 Pro with 48 GB of unified memory leaves about 36 GB for models. Expect about 8 tok/s, slow, but it works. The 24 GB version doesn't have room.
Can the Apple M5 Pro run Llama 3.3 70B?
Yes, with 64 GB or more. Llama 3.3 70B needs about 45 GB and the Apple M5 Pro with 64 GB of unified memory leaves about 48 GB for models. Expect about 4 tok/s, slow, but it works. The 24 and 48 GB versions don't have room.
Can the Apple M5 Pro run gpt-oss 120B?
No. gpt-oss 120B needs about 67 GB and the Apple M5 Pro has at most 64 GB of unified memory, of which about 48 GB is usable for models. The most capable model it runs well is Qwen3 30B-A3B, at about 54 tok/s.
Real runs on the Apple M5 Pro
Loading measured runs…
Generating a token reads the model's active weights from memory once, so speed is roughly memory bandwidth (307 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 runs are on the leaderboard.
The Used workstation + 2× Tesla P100 runs Qwen3 32B at about 20 tok/s, from $750 used.