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Can the Apple M2 Ultra (192 GB) run Solar Open 100B?

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

Yes, it runs well

Runs well. At Q4_K_M it needs about 76.3 GB of 144 GB usable, with an estimated speed of 35.2 tok/s.

Best quant
Q4_K_M
Generation speed
35.2 tok/s
Prompt processing
1,405 tok/s
First token (1K prompt)
0.7 s
Largest safe context
128K

Download Solar Open 100B

Recommended for the Apple M2 Ultra (192 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.

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.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.14.1 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.12.2 / 15
Total85.5 / 10085 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

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 54.8 GB 144 GB 57.9 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.8/15 GGUF (opens in a new tab)
Q3_K_M 64.0 GB 144 GB 45.6 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 30.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.3/15 GGUF (opens in a new tab)
Q4_K_M 76.3 GB 144 GB 35.2 tok/s Runs well 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 GGUF (opens in a new tab)
Q5_K_M 86.6 GB 144 GB 29.1 tok/s Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 12.8/15, Memory use 13.9/15 GGUF (opens in a new tab)
Q6_K 97.9 GB 144 GB 24.4 tok/s Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 11.7/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 123 GB 144 GB 17.9 tok/s Tight fit 85 ptsExcellent (S) · 85 of 100 points: Model quality 36.0/45, Memory fit 24.0/25, Speed 10.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
F16 219 GB 144 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

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.