Can NVIDIA RTX 5000 Ada run Qwen 2.5 14B?
14B parameter LLM model on 32GB GDDR6 ECC
VRAM Requirements
Qwen 2.5 14B is a 14B parameter model. At full precision (FP16), it requires 28GB of VRAM. Your NVIDIA RTX 5000 Ada has 32GB — enough to run it without any quantization.
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
With NVIDIA RTX 5000 Ada running Qwen 2.5 14B 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 14B
ollama run qwen2.5:14bThis downloads the model (~28GB). 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 ~28GB used.
NVIDIA RTX 5000 Ada Specs
Other GPUs That Run Qwen 2.5 14B
Other LLM Models on NVIDIA RTX 5000 Ada
About Qwen 2.5 14B
Good balance of quality and speed. Fits on 12–16GB GPUs at Q4-Q8.