Can NVIDIA GeForce RTX 4080 SUPER run Llama 3.1 8B?

8B parameter LLM model on 16GB GDDR6X

Yes — runs at full precision
~25-31 tok/sUsable
SpeedFastest possible inference
QualityMaximum quality, no degradation

VRAM Requirements

Llama 3.1 8B is a 8B parameter model. At full precision (FP16), it requires 16GB of VRAM. Your NVIDIA GeForce RTX 4080 SUPER has 16GB — enough to run it without any quantization.

FP16 (Full Precision)16GB (0GB free)

Maximum quality, no quantization

Q8 (8-bit)8GB (8GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)5GB (11GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 16GB GDDR6X at 736 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

With NVIDIA GeForce RTX 4080 SUPER running Llama 3.1 8B at full precision, you get the highest quality responses with no quantization artifacts. This is ideal for tasks requiring nuanced reasoning, creative writing, and complex analysis. You'll have the best possible experience with this model.

How to Set It Up

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Ollama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.

Step 2: Download and run Llama 3.1 8B

ollama run llama3.1:8b

This downloads the model (~16GB). First run takes a few minutes.

Step 3: Verify GPU is being used

nvidia-smi

Check that VRAM usage increases when the model loads. You should see ~16GB used.

NVIDIA GeForce RTX 4080 SUPER Specs

VRAM16GB GDDR6X
Memory Bandwidth736 GB/s
TDP320W
CUDA Cores10,240
Street Price~$950
AI Rating7/10

About Llama 3.1 8B

Great entry point. Runs well on 8GB+ GPUs at Q4.

Category: LLM · Parameters: 8B · CUDA required: No (runs via llama.cpp/GGUF)