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Can the NVIDIA GeForce RTX 4070 SUPER run Vicuna 13B v1.5?

61 ptsGood (B) · 61 of 100 points: Model quality 7.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 10.9 GB of 12.0 GB usable, with an estimated speed of 61.4 tok/s.

Best quant
Q3_K_M
Generation speed
61.4 tok/s
Prompt processing
1,963 tok/s
First token (1K prompt)
0.5 s
Largest safe context
4K

Download Vicuna 13B v1.5

Recommended for the NVIDIA GeForce RTX 4070 SUPER: Q3_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 vicuna:13b-v1.5-q3_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 Q3_K_M file (opens in a new tab)

huggingface.co/QuantFactory/vicuna-13b-v1.5-GGUF (opens in a new tab)

ollama run hf.co/QuantFactory/vicuna-13b-v1.5-GGUF:Q3_K_M

Original weights · Hugging Face

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

huggingface.co/lmsys/vicuna-13b-v1.5 (opens in a new tab)

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B 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.7.6 / 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.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
Total61.6 / 10061 ptsGood (B) · 61 of 100 points: Model quality 7.6/45, Memory fit 24.0/25, 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 9.8 GB 12.0 GB 78.0 tok/s Runs well 61 ptsGood (B) · 61 of 100 points: Model quality 6.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q3_K_M 10.9 GB 12.0 GB 61.4 tok/s Tight fit 61 ptsGood (B) · 61 of 100 points: Model quality 7.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 12.5 GB 12.0 GB 33.7 tok/s Runs with offload 47 ptsUsable (C) · 47 of 100 points: Model quality 8.6/45, Memory fit 10.0/25, Speed 13.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 13.8 GB 12.0 GB 17.2 tok/s Runs with offload 43 ptsUsable (C) · 43 of 100 points: Model quality 8.7/45, Memory fit 10.0/25, Speed 9.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 15.2 GB 12.0 GB 11.0 tok/s Heavy offload 35 ptsPoor (D) · 35 of 100 points: Model quality 8.9/45, Memory fit 4.0/25, Speed 7.9/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 18.4 GB 12.0 GB 6.0 tok/s Heavy offload 33 ptsPoor (D) · 33 of 100 points: Model quality 9.0/45, Memory fit 4.0/25, Speed 5.8/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 30.6 GB 12.0 GB 2.0 tok/s Heavy offload 31 ptsPoor (D) · 31 of 100 points: Model quality 9.0/45, Memory fit 4.0/25, Speed 3.3/15, 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.