Can NVIDIA Tesla P40 run Qwen 2.5 32B?
32B parameter LLM model on 24GB GDDR5X
VRAM Requirements
Qwen 2.5 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your NVIDIA Tesla P40 has 24GB, so you'll need to quantize it to 4-bit (Q4) to fit.
Maximum quality, no quantization
Near-lossless, ~50% size reduction
Good quality, ~75% size reduction
Recommended system RAM: 48GB DDR5 (2x GPU VRAM minimum for model overflow)
What This Means in Practice
At 4-bit quantization, Qwen 2.5 32B fits in NVIDIA Tesla P40's 24GB VRAM but with some quality trade-offs. Complex reasoning tasks and nuanced writing may show slight degradation. For casual chat, code assistance, and general queries, Q4 is perfectly usable. For critical work, consider a GPU with more VRAM to run at Q8.
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 qwen2.5:32b:q4_K_MThis downloads the Q4_K_M quantized version (~20GB). First run takes a few minutes to download.
Step 3: Verify GPU is being used
nvidia-smiCheck that VRAM usage increases when the model loads. You should see ~20GB used.
NVIDIA Tesla P40 Specs
Other GPUs That Run Qwen 2.5 32B
Other LLM Models on NVIDIA Tesla P40
About Qwen 2.5 32B
Strong reasoning in a more accessible size. Q4 fits on 24GB GPUs.