text model · GLM · macOS
GL Can I run GLM-4 9B on Apple M4 (16GB)?
Yes. GLM-4 9B runs on Apple M4 (16GB) at Q4_K_M (~7.3 GB of ~10.5 GB usable).
Runs at Q4_K_M using ~7.3 GB of ~10.5 GB usable.
- Q4_K_M needed
- ~7.3 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 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 vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
- Parameters
- 9B
- Q4_K_M size
- 5.82 GB
- Q8_0 size
- 9.31 GB
- Context
- 128k
- Ollama tag
- glm4:9b
- Memory
- 16 GB unified
- Usable for weights
- ~10.5 GB
- Best runtime
- Ollama (MLX backend, preview) / MLX direct
You could also run
Run GLM-4 9B on other hardware
FAQ
Can Apple M4 (16GB) run GLM-4 9B?
Yes. GLM-4 9B runs on Apple M4 (16GB) at Q4_K_M (~7.3 GB of ~10.5 GB usable).
How much memory does GLM-4 9B need?
Apple M4 (16GB) 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 macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
Sources
Memory figures are estimates. See methodology.