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Can the Apple M2 Ultra (192 GB) run DeepSeek V4 Flash (284B-A13B)?

83 ptsGreat (A) · 83 of 100 points: Model quality 29.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q2_K it needs about 134 GB of 144 GB usable, with an estimated speed of 53.4 tok/s.

Best quant
Q2_K
Generation speed
53.4 tok/s
Prompt processing
1,297 tok/s
First token (1K prompt)
0.8 s
Largest safe context
226K

Download DeepSeek V4 Flash (284B-A13B)

Recommended for the Apple M2 Ultra (192 GB): Q2_K. Every other quantization has its own download link in the table below.

Ollama

Ollama only offered this as a cloud model, and has since retired it. To run it locally, use the GGUF files below with llama.cpp or LM Studio.

Quantized files · GGUF

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

Download the Q2_K (UD-Q2_K_XL) files (opens in a new tab)

huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUF (opens in a new tab)

ollama run hf.co/unsloth/DeepSeek-V4-Flash-0731-GGUF

Original weights · Hugging Face

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

huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731 (opens in a new tab)

No sign-in needed.

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.29.6 / 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.15.0 / 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
Total83.6 / 10083 ptsGreat (A) · 83 of 100 points: Model quality 29.6/45, Memory fit 24.0/25, Speed 15.0/15, 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 M2 Ultra (192 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 134 GB 144 GB 53.4 tok/s Tight fit 83 ptsGreat (A) · 83 of 100 points: Model quality 29.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (UD-Q2_K_XL) · folder (opens in a new tab)
Q3_K_M 162 GB 144 GB 35.7 tok/s Heavy offload 68 ptsGood (B) · 68 of 100 points: Model quality 35.5/45, Memory fit 4.0/25, Speed 14.2/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q4_K_M 198 GB 144 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (UD-Q4_K_XL) · folder (opens in a new tab)
Q5_K_M 228 GB 144 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 files (opens in a new tab)
Q6_K 262 GB 144 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q8_0 335 GB 144 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
F16 621 GB 144 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.7/45, 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.