text model · Qwen2.5-Coder · Windows
Can I run Qwen2.5 Coder 32B on Nvidia GeForce RTX 4060 Ti (16GB)?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (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
- Ollama (CUDA) / llama.cpp CUDA
What you can run instead
Run Qwen2.5 Coder 32B on other hardware
FAQ
Can Nvidia GeForce RTX 4060 Ti (16GB) run Qwen2.5 Coder 32B?
No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.
How much memory does Qwen2.5 Coder 32B need?
Nvidia GeForce RTX 4060 Ti (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.