Can NVIDIA RTX 4000 Ada run Qwen 2.5 14B?
14B parameter LLM model on 20GB GDDR6
VRAM Requirements
Qwen 2.5 14B is a 14B parameter model. At full precision (FP16), it requires 28GB of VRAM. Your NVIDIA RTX 4000 Ada has 20GB, 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: 40GB DDR5 (2x GPU VRAM minimum for model overflow)
What This Means in Practice
Running Qwen 2.5 14B at 8-bit quantization on NVIDIA RTX 4000 Ada 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 14B
ollama run qwen2.5:14bThis downloads the model (~14GB). 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 ~14GB used.
NVIDIA RTX 4000 Ada Specs
Other GPUs That Run Qwen 2.5 14B
Other LLM Models on NVIDIA RTX 4000 Ada
About Qwen 2.5 14B
Good balance of quality and speed. Fits on 12–16GB GPUs at Q4-Q8.