DeepSeek R1 (671B) on Apple M3 Ultra (512 GB)

Can the Apple M3 Ultra (512 GB) run DeepSeek R1 (671B)?

82 pts

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 361 GB of 384 GB usable, with an estimated speed of 15.1 tok/s.

Best quant: Q3_K_M
Generation speed: 15.1 tok/s
Prompt processing: 476 tok/s
First token (1K prompt): 2.2 s
Largest safe context: 128K

Download DeepSeek R1 (671B)

Recommended for the Apple M3 Ultra (512 GB): Q3_K_M. 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 deepseek-r1:671b

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 Q3_K_M files (opens in a new tab)

huggingface.co/unsloth/DeepSeek-R1-GGUF (opens in a new tab)

ollama run hf.co/unsloth/DeepSeek-R1-GGUF

Original weights · Hugging Face

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

huggingface.co/deepseek-ai/DeepSeek-R1 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/deepseek-ai/DeepSeek-R1 (opens in a new tab)

git clone https://github.com/deepseek-ai/DeepSeek-R1

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the A 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.	34.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	9.2 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	83.0 / 100	82 ptsGreat (A) · 82 of 100 points: Model quality 34.8/45, Memory fit 24.0/25, Speed 9.2/15, Memory use 15.0/15

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

Every quantization on the Apple M3 Ultra (512 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	300 GB	384 GB	19.2 tok/s	Runs well	79 ptsGreat (A) · 79 of 100 points: Model quality 29.0/45, Memory fit 25.0/25, Speed 10.4/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q3_K_M`	361 GB	384 GB	15.1 tok/s	Tight fit	82 ptsGreat (A) · 82 of 100 points: Model quality 34.8/45, Memory fit 24.0/25, Speed 9.2/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q4_K_M`	441 GB	384 GB	9.9 tok/s	Heavy offload	65 ptsGood (B) · 65 of 100 points: Model quality 39.3/45, Memory fit 4.0/25, Speed 7.5/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q5_K_M`	508 GB	384 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q6_K`	582 GB	384 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q8_0`	743 GB	384 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`F16`	1,374 GB	384 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (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.