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Can the Apple M3 Ultra (256 GB) run Solar Open 100B?

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

Yes, it runs well

Runs well. At Q4_K_M it needs about 80.2 GB of 192 GB usable, with an estimated speed of 36.1 tok/s.

Best quant
Q4_K_M
Generation speed
36.1 tok/s
Prompt processing
1,467 tok/s
First token (1K prompt)
0.7 s
Largest safe context
128K

Download Solar Open 100B

Recommended for the Apple M3 Ultra (256 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.14.2 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.9.6 / 15
Total83.1 / 10083 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

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the Apple M3 Ultra (256 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 58.6 GB 192 GB 59.2 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 25.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.0/15 GGUF (opens in a new tab)
Q3_K_M 67.9 GB 192 GB 46.6 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 30.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.2/15 GGUF (opens in a new tab)
Q4_K_M 80.2 GB 192 GB 36.1 tok/s Runs well 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 GGUF (opens in a new tab)
Q5_K_M 90.5 GB 192 GB 29.8 tok/s Runs well 83 ptsGreat (A) · 83 of 100 points: Model quality 34.9/45, Memory fit 25.0/25, Speed 12.9/15, Memory use 10.9/15 GGUF (opens in a new tab)
Q6_K 102 GB 192 GB 25.0 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 11.9/15, Memory use 12.2/15 GGUF (opens in a new tab)
Q8_0 126 GB 192 GB 18.4 tok/s Runs well 86 ptsExcellent (S) · 86 of 100 points: Model quality 36.0/45, Memory fit 25.0/25, Speed 10.2/15, Memory use 15.0/15 GGUF files (opens in a new tab)
F16 223 GB 192 GB 7.2 tok/s Heavy offload 61 ptsGood (B) · 61 of 100 points: Model quality 36.0/45, Memory fit 4.0/25, Speed 6.4/15, Memory use 15.0/15 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.