GPUs/NVIDIA RTX A6000/Qwen 2.5 Coder 32B

Can NVIDIA RTX A6000 run Qwen 2.5 Coder 32B?

32B parameter Code model on 48GB GDDR6

Yes — runs at 8-bit quantization
~14-18 tok/sSlow
SpeedFast inference, near-native speed
QualityNear-lossless — virtually identical to FP16

VRAM Requirements

Qwen 2.5 Coder 32B is a 32B parameter model. At full precision (FP16), it requires 64GB of VRAM. Your NVIDIA RTX A6000 has 48GB, so you'll need to quantize it to 8-bit (Q8) to fit.

FP16 (Full Precision)64GB (need 16GB more)

Maximum quality, no quantization

Q8 (8-bit)32GB (16GB free)

Near-lossless, ~50% size reduction

Q4 (4-bit)20GB (28GB free)

Good quality, ~75% size reduction

Your GPU VRAM: 48GB GDDR6 at 768 GB/s bandwidth
Recommended system RAM: 96GB DDR5 (2x GPU VRAM minimum for model overflow)

What This Means in Practice

Qwen 2.5 Coder 32B at this precision on NVIDIA RTX A6000 gives excellent code completion and generation. Fast enough for real-time IDE integration. Handles complex refactoring, multi-file edits, and long-context code understanding.

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

This downloads the model (~32GB). First run takes a few minutes.

Step 3: Verify GPU is being used

nvidia-smi

Check that VRAM usage increases when the model loads. You should see ~32GB used.

NVIDIA RTX A6000 Specs

VRAM48GB GDDR6
Memory Bandwidth768 GB/s
TDP300W
CUDA Cores10,752
Street Price~$3800
AI Rating9/10

Other Code Models on NVIDIA RTX A6000

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)