GPUs/NVIDIA GeForce RTX 3090/Qwen 2.5 Coder 32B

Can NVIDIA GeForce RTX 3090 run Qwen 2.5 Coder 32B?

32B parameter Code model on 24GB GDDR6X

Yes — runs at 4-bit quantization
~25-31 tok/sUsable
SpeedModerate speed, usable for interactive chat
QualityGood quality with slight degradation on complex reasoning

VRAM Requirements

Qwen 2.5 Coder 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your NVIDIA GeForce RTX 3090 has 24GB, so you'll need to quantize it to 4-bit (Q4) to fit.

FP16 (Full Precision)64GB (need 40GB more)

Maximum quality, no quantization

Q8 (8-bit)32GB (need 8GB more)

Near-lossless, ~50% size reduction

Q4 (4-bit)20GB (4GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 24GB GDDR6X at 936 GB/s bandwidth
Recommended system RAM: 48GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Qwen 2.5 Coder 32B at Q4 on NVIDIA GeForce RTX 3090 works for code completion but complex multi-file operations may show quality drops. Still very usable for day-to-day coding assistance. Consider a larger VRAM GPU for professional code generation workflows.

How to Set It Up

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Ollama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.

Step 2: Download and run Qwen 2.5 Coder 32B

ollama run qwen2.5:32b:q4_K_M

This downloads the Q4_K_M quantized version (~20GB). First run takes a few minutes to download.

Step 3: Verify GPU is being used

nvidia-smi

Check that VRAM usage increases when the model loads. You should see ~20GB used.

NVIDIA GeForce RTX 3090 Specs

VRAM24GB GDDR6X
Memory Bandwidth936 GB/s
TDP350W
CUDA Cores10,496
Street Price~$900
AI Rating7/10

Other Code Models on NVIDIA GeForce RTX 3090

About Qwen 2.5 Coder 32B

Best open-source coding model. Needs 24GB+ for good quality.

Category: Code · Parameters: 32B · CUDA required: No (runs via llama.cpp/GGUF)