Can AMD Radeon RX 6800 XT run Llama 3.1 8B?

8B parameter LLM model on 16GB GDDR6

Yes — runs at full precision
~10-12 tok/sSlow
SpeedFastest possible inference
QualityMaximum quality, no degradation
AMD GPUs lack CUDA. While Llama 3.1 8B can technically run via llama.cpp/GGUF, the setup is more complex and less optimized than on NVIDIA hardware.

VRAM Requirements

Llama 3.1 8B is a 8B parameter model. At full precision (FP16), it requires 16GB of VRAM. Your AMD Radeon RX 6800 XT 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 GDDR6 at 512 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

With AMD Radeon RX 6800 XT 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

rocm-smi

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

AMD Radeon RX 6800 XT Specs

VRAM16GB GDDR6
Memory Bandwidth512 GB/s
TDP300W
CUDA CoresN/A
Street Price~$320
AI Rating2/10

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)