text model · Muse · iOS
Can I run Muse Glimmer 30B on iPhone Air?
No. Muse Glimmer 30B needs ~18.2 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
Needs ~18.2 GB even at Q4_K_M, but only ~8 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 10.2 GB: Muse Glimmer 30B needs roughly 18.2 GB at Q4_K_M and iPhone Air leaves only about 8 GB usable for a model. The lightest tracked hardware that runs Muse Glimmer 30B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Muse Glimmer 30B on Nvidia GeForce RTX 4090 (24GB).
- Q4_K_M needed
- ~18.2 GB
- Usable on device
- ~8 GB
- Device memory
- 12 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
- 30B
- Q4_K_M size
- 16.12 GB
- Q8_0 size
- 30.12 GB
- Context
- 128k
- Ollama tag
- muse-glimmer:30b
- Memory
- 12 GB unified
- Usable for weights
- ~8 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run Muse Glimmer 30B on other hardware
FAQ
Can iPhone Air run Muse Glimmer 30B?
No. Muse Glimmer 30B needs ~18.2 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
How much memory does Muse Glimmer 30B need?
iPhone Air does not have enough memory. At Q4_K_M the weights are ~16.12 GB; with KV cache and runtime overhead, budget ~18.2 GB at a 4k context.
What is the best tool to run Muse Glimmer 30B 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/muse-glimmer-30b/iphone-air) Sources
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.