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Can the NVIDIA GeForce RTX 4070 SUPER run SOLAR 10.7B Instruct?

72 ptsGreat (A) · 72 of 100 points: Model quality 17.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q5_K_M it needs about 9.6 GB of 12.0 GB usable, with an estimated speed of 47.6 tok/s.

Best quant
Q5_K_M
Generation speed
47.6 tok/s
Prompt processing
2,382 tok/s
First token (1K prompt)
0.4 s
Largest safe context
4K

Download SOLAR 10.7B Instruct

Recommended for the NVIDIA GeForce RTX 4070 SUPER: Q5_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run solar:10.7b-instruct-v1-q5_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q5_K_M file (opens in a new tab)

huggingface.co/QuantFactory/SOLAR-10.7B-Instruct-v1.0-GGUF (opens in a new tab)

ollama run hf.co/QuantFactory/SOLAR-10.7B-Instruct-v1.0-GGUF:Q5_K_M

Original weights · Hugging Face

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

huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0 (opens in a new tab)

No sign-in needed.

Links checked 7 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.17.5 / 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
Total72.5 / 10072 ptsGreat (A) · 72 of 100 points: Model quality 17.5/45, 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 NVIDIA GeForce RTX 4070 SUPER

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 6.3 GB 12.0 GB 94.7 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q3_K_M 7.3 GB 12.0 GB 74.5 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 15.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.0/15 GGUF (opens in a new tab)
Q4_K_M 8.6 GB 12.0 GB 57.7 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 17.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 9.6 GB 12.0 GB 47.6 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 17.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 10.8 GB 12.0 GB 40.0 tok/s Tight fit 71 ptsGood (B) · 71 of 100 points: Model quality 17.8/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 13.4 GB 12.0 GB 16.3 tok/s Runs with offload 52 ptsUsable (C) · 52 of 100 points: Model quality 18.0/45, Memory fit 10.0/25, Speed 9.6/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 23.5 GB 12.0 GB 3.0 tok/s Heavy offload 41 ptsPoor (D) · 41 of 100 points: Model quality 18.0/45, Memory fit 4.0/25, Speed 4.1/15, Memory use 15.0/15 Original weights (opens in a new tab)

Memory figures assume 4K 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.