text model · GLM · Windows
Can I run GLM-4.5-Air on 16GB RAM Laptop (CPU/iGPU only)?
No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.
Needs ~71.8 GB even at Q4_K_M, but only ~12 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 59.8 GB: GLM-4.5-Air needs roughly 71.8 GB at Q4_K_M and 16GB RAM Laptop (CPU/iGPU only) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs GLM-4.5-Air is the Apple M4 Max (128GB) at 128 GB. See GLM-4.5-Air on Apple M4 Max (128GB).
- Q4_K_M needed
- ~71.8 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
Which quant fits
How to run it
On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).
- Parameters
- 106B (MoE, 12B active)
- Q4_K_M size
- 68.45 GB
- Q8_0 size
- 109.39 GB
- Context
- 128k
- Memory
- 16 GB ram
- Usable for weights
- ~12 GB
- Power draw
- ~28 W
- Best runtime
- Ollama (llama.cpp backend)
What you can run instead
Run GLM-4.5-Air on other hardware
FAQ
Can 16GB RAM Laptop (CPU/iGPU only) run GLM-4.5-Air?
No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.
How much memory does GLM-4.5-Air need?
16GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~68.45 GB; with KV cache and runtime overhead, budget ~71.8 GB at a 4k context. It is a Mixture-of-Experts model (106B total / 12B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run GLM-4.5-Air 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.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/glm-4.5-air/laptop-16gb) Sources
- artificialanalysis.ai
- docs.z.ai
- en.wikipedia.org
- huggingface.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF
- huggingface.co/bartowski/zai-org_GLM-4.5-Air-GGUF
- huggingface.co/zai-org
- llm-stats.com
- lmstudio.ai
- notebookcheck.net
- ollama.com
- ollama.com/library/llama3.1:8b
- ollama.com/library/mistral:7b
- pcworld.com
- techpowerup.com
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.