GPUs/NVIDIA Tesla P40/Llama 3.1 8B

Can NVIDIA Tesla P40 run Llama 3.1 8B?

8B parameter LLM model on 24GB GDDR5X

Yes — runs at full precision
~7-9 tok/sSlow
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 Tesla P40 has 24GB — enough to run it without any quantization.

FP16 (Full Precision)16GB (8GB free)

Maximum quality, no quantization

Q8 (8-bit)8GB (16GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)5GB (19GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 24GB GDDR5X at 346 GB/s bandwidth
Recommended system RAM: 48GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

With NVIDIA Tesla P40 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 Tesla P40 Specs

VRAM24GB GDDR5X
Memory Bandwidth346 GB/s
TDP250W
CUDA Cores3,840
Street Price~$300
AI Rating5/10

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)