Can NVIDIA A100 80GB run Qwen 2.5 32B?
32B parameter LLM model on 80GB HBM2e
VRAM Requirements
Qwen 2.5 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your NVIDIA A100 80GB has 80GB — enough to run it without any quantization.
Maximum quality, no quantization
Near-lossless, ~50% size reduction
Good quality, ~75% size reduction
Recommended system RAM: 160GB DDR5 (2x GPU VRAM minimum for model overflow)
What This Means in Practice
With NVIDIA A100 80GB running Qwen 2.5 32B 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 | shOllama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.
Step 2: Download and run Qwen 2.5 32B
ollama run qwen2.5:32bThis downloads the model (~64GB). First run takes a few minutes.
Step 3: Verify GPU is being used
nvidia-smiCheck that VRAM usage increases when the model loads. You should see ~64GB used.
NVIDIA A100 80GB Specs
Other GPUs That Run Qwen 2.5 32B
Other LLM Models on NVIDIA A100 80GB
About Qwen 2.5 32B
Strong reasoning in a more accessible size. Q4 fits on 24GB GPUs.