Can NVIDIA GeForce RTX 5090 run Qwen 2.5 32B?
32B parameter LLM model on 32GB GDDR7
VRAM Requirements
Qwen 2.5 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your NVIDIA GeForce RTX 5090 has 32GB, so you'll need to quantize it to 8-bit (Q8) to fit.
Maximum quality, no quantization
Near-lossless, ~50% size reduction
Good quality, ~75% size reduction
Recommended system RAM: 64GB DDR5 (2x GPU VRAM minimum for model overflow)
What This Means in Practice
Running Qwen 2.5 32B at 8-bit quantization on NVIDIA GeForce RTX 5090 gives you virtually identical quality to full precision while using roughly half the VRAM. Most users cannot distinguish Q8 output from FP16. This is the recommended precision for daily use — it's the best balance of quality and resource usage.
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 (~32GB). 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 ~32GB used.
NVIDIA GeForce RTX 5090 Specs
Other GPUs That Run Qwen 2.5 32B
Other LLM Models on NVIDIA GeForce RTX 5090
About Qwen 2.5 32B
Strong reasoning in a more accessible size. Q4 fits on 24GB GPUs.