text model · Qwen3 · Windows
Can I run Qwen3 235B A22B on Nvidia GeForce RTX 4060 Ti (16GB)?
No. Qwen3 235B A22B needs ~136.9 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.
Needs ~136.9 GB even at Q4_K_M, but only ~15 GB is usable.
- Q4_K_M needed
- ~136.9 GB
- Usable on device
- ~15 GB
- Device memory
- 16 GB
- Parameters
- 235B (MoE, 22B active)
- Q4_K_M size
- 132.39 GB
- Context
- 128k
- Ollama tag
- qwen3:235b
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
What you can run instead
Run Qwen3 235B A22B on other hardware
FAQ
Can Nvidia GeForce RTX 4060 Ti (16GB) run Qwen3 235B A22B?
No. Qwen3 235B A22B needs ~136.9 GB even at Q4_K_M, but Nvidia GeForce RTX 4060 Ti (16GB) only has ~15 GB usable.
How much memory does Qwen3 235B A22B need?
Nvidia GeForce RTX 4060 Ti (16GB) does not have enough memory. At Q4_K_M the weights are ~132.39 GB; with KV cache and runtime overhead, budget ~136.9 GB at a 4k context. It is a Mixture-of-Experts model (235B total / 22B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Qwen3 235B A22B 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.