Can NVIDIA GeForce RTX 4080 run Mistral 7B?

7B parameter LLM model on 16GB GDDR6X

Yes — runs at full precision
~28-35 tok/sUsable
SpeedFastest possible inference
QualityMaximum quality, no degradation

VRAM Requirements

Mistral 7B is a 7B parameter model. At full precision (FP16), it requires 14GB of VRAM. Your NVIDIA GeForce RTX 4080 has 16GB — enough to run it without any quantization.

FP16 (Full Precision)14GB (2GB free)

Maximum quality, no quantization

Q8 (8-bit)7GB (9GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)4.5GB (12GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 16GB GDDR6X at 717 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 running Mistral 7B 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 Mistral 7B

ollama run mistral:7b

This downloads the model (~14GB). 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 ~14GB used.

NVIDIA GeForce RTX 4080 Specs

VRAM16GB GDDR6X
Memory Bandwidth717 GB/s
TDP320W
CUDA Cores9,728
Street Price~$850
AI Rating7/10

About Mistral 7B

Fast and efficient. Runs on virtually any modern GPU.

Category: LLM · Parameters: 7B · CUDA required: No (runs via llama.cpp/GGUF)