Can NVIDIA A100 80GB run Mistral 7B?

7B parameter LLM model on 80GB HBM2e

Yes — runs at full precision
~87-107 tok/sExcellent
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 A100 80GB has 80GB — enough to run it without any quantization.

FP16 (Full Precision)14GB (66GB free)

Maximum quality, no quantization

Q8 (8-bit)7GB (73GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)4.5GB (76GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 80GB HBM2e at 2039 GB/s bandwidth
Recommended system RAM: 160GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

With NVIDIA A100 80GB 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 A100 80GB Specs

VRAM80GB HBM2e
Memory Bandwidth2039 GB/s
TDP300W
CUDA Cores6,912
Street Price~$8000
AI Rating10/10

About Mistral 7B

Fast and efficient. Runs on virtually any modern GPU.

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