text model · GLM · iOS
Can I run GLM-4.5-Air on iPhone 17?
No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
Needs ~71.8 GB even at Q4_K_M, but only ~4.5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 67.3 GB: GLM-4.5-Air needs roughly 71.8 GB at Q4_K_M and iPhone 17 leaves only about 4.5 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
- ~4.5 GB
- Device memory
- 8 GB
Which quant fits
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 106B (MoE, 12B active)
- Q4_K_M size
- 68.45 GB
- Q8_0 size
- 109.39 GB
- Context
- 128k
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run GLM-4.5-Air on other hardware
FAQ
Can iPhone 17 run GLM-4.5-Air?
No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
How much memory does GLM-4.5-Air need?
iPhone 17 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 iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
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/iphone-17) Sources
- apple.com
- artificialanalysis.ai
- developer.apple.com
- docs.z.ai
- en.wikipedia.org/wiki/Apple_A19
- en.wikipedia.org/wiki/IPhone_17
- enclaveai.app
- github.com/a-ghorbani
- github.com/google-ai-edge
- github.com/mainframecomputer
- huggingface.co/bartowski
- huggingface.co/zai-org
- layla-network.ai
- llm-stats.com
- macrumors.com
- privatellm.app
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.