Llama 2 13B Chat on NVIDIA GeForce RTX 4080 SUPER

Can the NVIDIA GeForce RTX 4080 SUPER run Llama 2 13B Chat?

66 pts

Yes, it runs well

Runs well. At Q4_K_M it needs about 12.7 GB of 16.0 GB usable, with an estimated speed of 69.4 tok/s.

Best quant: Q4_K_M
Generation speed: 69.4 tok/s
Prompt processing: 2,887 tok/s
First token (1K prompt): 0.4 s
Largest safe context: 4K

Download Llama 2 13B Chat

Recommended for the NVIDIA GeForce RTX 4080 SUPER: Q4_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 llama2:13b-chat-q4_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 Q4_K_M file (opens in a new tab)

huggingface.co/TheBloke/Llama-2-13B-chat-GGUF (opens in a new tab)

ollama run hf.co/TheBloke/Llama-2-13B-chat-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/meta-llama/Llama-2-13b-chat-hf (opens in a new tab)

Free Hugging Face account needed: request access on the model page, and Meta approves it (usually within minutes to a few hours).

Official repo · GitHub

Reference code, inference scripts and docs from Meta. The weights themselves download from Hugging Face.

github.com/meta-llama/llama (opens in a new tab)

git clone https://github.com/meta-llama/llama

Meta’s original Llama 2 repo (now archived).

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.	11.1 / 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
Total	66.1 / 100	66 ptsGood (B) · 66 of 100 points: Model quality 11.1/45, 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 4080 SUPER

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	10.0 GB	16.0 GB	114 tok/s	Runs well	62 ptsGood (B) · 62 of 100 points: Model quality 8.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.4/15	GGUF (opens in a new tab)
`Q3_K_M`	11.1 GB	16.0 GB	89.7 tok/s	Runs well	64 ptsGood (B) · 64 of 100 points: Model quality 9.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q4_K_M`	12.7 GB	16.0 GB	69.4 tok/s	Runs well	66 ptsGood (B) · 66 of 100 points: Model quality 11.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	14.0 GB	16.0 GB	57.3 tok/s	Tight fit	65 ptsGood (B) · 65 of 100 points: Model quality 11.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q6_K`	15.4 GB	16.0 GB	48.1 tok/s	Tight fit	65 ptsGood (B) · 65 of 100 points: Model quality 11.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q8_0`	18.6 GB	16.0 GB	12.4 tok/s	Runs with offload	45 ptsUsable (C) · 45 of 100 points: Model quality 11.7/45, Memory fit 10.0/25, Speed 8.3/15, Memory use 15.0/15	GGUF (opens in a new tab)
`F16`	30.8 GB	16.0 GB	2.4 tok/s	Heavy offload	34 ptsPoor (D) · 34 of 100 points: Model quality 11.7/45, Memory fit 4.0/25, Speed 3.7/15, 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

66 ptsGood (B) · 66 of 100 points: Model quality 11.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q8_0 · 44.9 tok/s
66 ptsGood (B) · 66 of 100 points: Model quality 11.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q8_0 · 48.4 tok/s
66 ptsGood (B) · 66 of 100 points: Model quality 11.7/45, Memory fit 25.0/25, Speed 14.9/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q8_0 · 39.7 tok/s
66 ptsGood (B) · 66 of 100 points: Model quality 11.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 9070 XT Q4_K_M · 52.0 tok/s
66 ptsGood (B) · 66 of 100 points: Model quality 11.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER Q4_K_M · 63.4 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.