Can the NVIDIA GB10 (128 GB) run Solar Open 100B?

82 pts

Yes, it runs well

Runs well. At Q4_K_M it needs about 74.0 GB of 115 GB usable, with an estimated speed of 14.0 tok/s.

Best quant: Q4_K_M
Generation speed: 14.0 tok/s
Prompt processing: 1,860 tok/s
First token (1K prompt): 0.6 s
Largest safe context: 128K

Download Solar Open 100B

Recommended for the NVIDIA GB10 (128 GB): Q4_K_M. 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 Q4_K_M file (opens in a new tab)

huggingface.co/mradermacher/Solar-Open-100B-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/Solar-Open-100B-i1-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/upstage/Solar-Open-100B (opens in a new tab)

No sign-in needed.

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.	34.2 / 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.	8.9 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	14.8 / 15
Total	82.9 / 100	82 ptsGreat (A) · 82 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 8.9/15, Memory use 14.8/15

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`	52.5 GB	115 GB	22.9 tok/s	Runs well	72 ptsGreat (A) · 72 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 11.4/15, Memory use 10.5/15	GGUF (opens in a new tab)
`Q3_K_M`	61.7 GB	115 GB	18.1 tok/s	Runs well	77 ptsGreat (A) · 77 of 100 points: Model quality 30.2/45, Memory fit 25.0/25, Speed 10.1/15, Memory use 12.4/15	GGUF (opens in a new tab)
`Q4_K_M`	74.0 GB	115 GB	14.0 tok/s	Runs well	82 ptsGreat (A) · 82 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 8.9/15, Memory use 14.8/15	GGUF (opens in a new tab)
`Q5_K_M`	84.3 GB	115 GB	11.5 tok/s	Runs well	82 ptsGreat (A) · 82 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 8.1/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q6_K`	95.6 GB	115 GB	9.7 tok/s	Runs well	83 ptsGreat (A) · 83 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 7.4/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q8_0`	120 GB	115 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 10.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF files (opens in a new tab)
`F16`	217 GB	115 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 10.8/45, 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

89 ptsExcellent (S) · 89 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell Q5_K_M · 75.7 tok/s
85 ptsExcellent (S) · 85 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 11.6/15, Memory use 15.0/15 Apple M4 Max (128 GB) Q4_K_M · 24.0 tok/s
85 ptsExcellent (S) · 85 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 14.1/15, Memory use 12.2/15 Apple M2 Ultra (192 GB) Q4_K_M · 35.2 tok/s
83 ptsGreat (A) · 83 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 14.2/15, Memory use 9.6/15 Apple M3 Ultra (256 GB) Q4_K_M · 36.1 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 8.0/15, Memory use 15.0/15 AMD Ryzen AI Max+ 395 (128 GB) Q4_K_M · 11.3 tok/s

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.