Check my GPU

on

Can the Apple M1 Ultra (128 GB) run Qwen3-Next 80B-A3B Thinking?

93 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 75.2 GB of 96.0 GB usable, with an estimated speed of 97.8 tok/s.

Best quant
Q6_K
Generation speed
97.8 tok/s
Prompt processing
4,340 tok/s
First token (1K prompt)
0.3 s
Largest safe context
256K

Download Qwen3-Next 80B-A3B Thinking

Recommended for the Apple M1 Ultra (128 GB): Q6_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q6_K file (opens in a new tab)

huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen3-Next-80B-A3B-Thinking-GGUF:Q6_K

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking (opens in a new tab)

No sign-in needed.

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

How the S 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.38.3 / 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.15.0 / 15
Total93.3 / 10093 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, 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 M1 Ultra (128 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 41.0 GB 96.0 GB 231 tok/s Runs well 76 ptsGreat (A) · 76 of 100 points: Model quality 27.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.9/15 GGUF files (opens in a new tab)
Q3_K_M 48.3 GB 96.0 GB 182 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.6/15 GGUF files (opens in a new tab)
Q4_K_M 58.1 GB 96.0 GB 141 tok/s Runs well 90 ptsExcellent (S) · 90 of 100 points: Model quality 36.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.0/15 GGUF (opens in a new tab)
Q5_K_M 66.2 GB 96.0 GB 116 tok/s Runs well 92 ptsExcellent (S) · 92 of 100 points: Model quality 37.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 75.2 GB 96.0 GB 97.8 tok/s Runs well 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 94.7 GB 96.0 GB 71.7 tok/s Tight fit 92 ptsExcellent (S) · 92 of 100 points: Model quality 38.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 171 GB 96.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.