text model · Qwen2.5-Coder · Windows
Can I run Qwen2.5 Coder 32B on Nvidia GeForce RTX 4080 (16GB)?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.
Needs ~20.7 GB even at Q4_K_M, but only ~15 GB is usable.
- Q4_K_M needed
- ~20.7 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Parameters
- 32B
- Q4_K_M size
- 18.49 GB
- Q8_0 size
- 32.43 GB
- Context
- 32k
- Ollama tag
- qwen2.5-coder:32b
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
What you can run instead
Run Qwen2.5 Coder 32B on other hardware
FAQ
Can Nvidia GeForce RTX 4080 (16GB) run Qwen2.5 Coder 32B?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.
How much memory does Qwen2.5 Coder 32B need?
Nvidia GeForce RTX 4080 (16GB) does not have enough memory. At Q4_K_M the weights are ~18.49 GB; with KV cache and runtime overhead, budget ~20.7 GB at a 4k context.
What is the best tool to run Qwen2.5 Coder 32B on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Sources
Memory figures are estimates. See methodology.