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Can the Apple M5 Max (64 GB) run Qwen2.5 7B Instruct?

69 ptsGood (B) · 69 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.2/15

Yes, it runs well

Runs well. At Q8_0 it needs about 13.0 GB of 48.0 GB usable, with an estimated speed of 43.4 tok/s.

Best quant
Q8_0
Generation speed
43.4 tok/s
Prompt processing
1,538 tok/s
First token (1K prompt)
0.7 s
Largest safe context
32K

Download Qwen2.5 7B Instruct

Recommended for the Apple M5 Max (64 GB): Q8_0. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run qwen2.5:7b-instruct-q8_0

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q8_0 file (opens in a new tab)

huggingface.co/Qwen/Qwen2.5-7B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen2.5-7B-Instruct-GGUF:Q8_0

Original weights · Hugging Face

Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.

huggingface.co/Qwen/Qwen2.5-7B-Instruct (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.

github.com/QwenLM/Qwen3 (opens in a new tab)

git clone https://github.com/QwenLM/Qwen3

Qwen’s main repo, renamed from Qwen2.5 to Qwen3; it still documents Qwen2.5.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.23.4 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.6.2 / 15
Total69.6 / 10069 ptsGood (B) · 69 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.2/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the Apple M5 Max (64 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 8.0 GB 48.0 GB 140 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 16.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.8/15 GGUF (opens in a new tab)
Q3_K_M 8.6 GB 48.0 GB 110 tok/s Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 19.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.2/15 GGUF (opens in a new tab)
Q4_K_M 9.6 GB 48.0 GB 85.2 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 22.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.6/15 GGUF · part 1 of 2 (opens in a new tab)
Q5_K_M 10.3 GB 48.0 GB 70.4 tok/s Runs well 67 ptsGood (B) · 67 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.0/15 GGUF · part 1 of 2 (opens in a new tab)
Q6_K 11.2 GB 48.0 GB 59.1 tok/s Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 23.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.4/15 GGUF · part 1 of 2 (opens in a new tab)
Q8_0 13.0 GB 48.0 GB 43.4 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.2/15 GGUF · part 1 of 3 (opens in a new tab)
F16 20.1 GB 48.0 GB 20.0 tok/s Runs well 68 ptsGood (B) · 68 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 10.6/15, Memory use 9.7/15 GGUF · part 1 of 4 (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.