text model · GLM · Windows
GL Can I run GLM-4 9B on Nvidia GeForce RTX 3060 (12GB)?
Yes. GLM-4 9B runs on Nvidia GeForce RTX 3060 (12GB) at Q4_K_M (~7.3 GB of ~11 GB usable).
Runs at Q4_K_M using ~7.3 GB of ~11 GB usable. You have room for Q8_0 for higher quality.
- Q4_K_M needed
- ~7.3 GB
- Usable on device
- ~11 GB
- Device memory
- 12 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
ollama run glm4:9b llama-cli -hf bartowski/glm-4-9b-chat-GGUF:Q4_K_M lms get bartowski/glm-4-9b-chat-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 9B
- Q4_K_M size
- 5.82 GB
- Q8_0 size
- 9.31 GB
- Context
- 128k
- Ollama tag
- glm4:9b
- Memory
- 12 GB vram
- Usable for weights
- ~11 GB
- Best runtime
- Ollama (CUDA) / llama.cpp CUDA
You could also run
Run GLM-4 9B on other hardware
FAQ
Can Nvidia GeForce RTX 3060 (12GB) run GLM-4 9B?
Yes. GLM-4 9B runs on Nvidia GeForce RTX 3060 (12GB) at Q4_K_M (~7.3 GB of ~11 GB usable).
How much memory does GLM-4 9B need?
Nvidia GeForce RTX 3060 (12GB) has room to spare. At Q4_K_M the weights are ~5.82 GB; with KV cache and runtime overhead, budget ~7.3 GB at a 4k context.
What is the best tool to run GLM-4 9B 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.