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Can the NVIDIA GB10 (128 GB) run MiniMax M2 (230B-A10B)?

79 ptsGreat (A) · 79 of 100 points: Model quality 28.0/45, Memory fit 24.0/25, Speed 12.4/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q2_K it needs about 103 GB of 115 GB usable, with an estimated speed of 27.5 tok/s.

Best quant
Q2_K
Generation speed
27.5 tok/s
Prompt processing
2,232 tok/s
First token (1K prompt)
0.5 s
Largest safe context
53K

Download MiniMax M2 (230B-A10B)

Recommended for the NVIDIA GB10 (128 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 files (opens in a new tab)

huggingface.co/unsloth/MiniMax-M2-GGUF (opens in a new tab)

ollama run hf.co/unsloth/MiniMax-M2-GGUF

Original weights · Hugging Face

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

huggingface.co/MiniMaxAI/MiniMax-M2 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/MiniMax-AI/MiniMax-M2 (opens in a new tab)

git clone https://github.com/MiniMax-AI/MiniMax-M2

Links checked 6 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.28.0 / 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.12.4 / 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
Total79.5 / 10079 ptsGreat (A) · 79 of 100 points: Model quality 28.0/45, Memory fit 24.0/25, Speed 12.4/15, 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 NVIDIA GB10 (128 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 103 GB 115 GB 27.5 tok/s Tight fit 79 ptsGreat (A) · 79 of 100 points: Model quality 28.0/45, Memory fit 24.0/25, Speed 12.4/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q3_K_M 124 GB 115 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q4_K_M 151 GB 115 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q5_K_M 174 GB 115 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q6_K 199 GB 115 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q8_0 254 GB 115 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)
F16 469 GB 115 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) 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.