text model · Granite · iOS
Can I run Granite 4.0 H Small on iPhone 17?
No. Granite 4.0 H Small needs ~20.3 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
Needs ~20.3 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 15.8 GB: Granite 4.0 H Small needs roughly 20.3 GB at Q4_K_M and iPhone 17 leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs Granite 4.0 H Small is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Granite 4.0 H Small on Nvidia GeForce RTX 4090 (24GB).
- Q4_K_M needed
- ~20.3 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
- 32B (MoE, 9B active)
- Q4_K_M size
- 18.14 GB
- Q8_0 size
- 31.91 GB
- Context
- 128k
- Ollama tag
- granite4:32b-a9b-h
- 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 Granite 4.0 H Small on other hardware
FAQ
Can iPhone 17 run Granite 4.0 H Small?
No. Granite 4.0 H Small needs ~20.3 GB even at Q4_K_M, but iPhone 17 only has ~4.5 GB usable.
How much memory does Granite 4.0 H Small need?
iPhone 17 does not have enough memory. At Q4_K_M the weights are ~18.14 GB; with KV cache and runtime overhead, budget ~20.3 GB at a 4k context. It is a Mixture-of-Experts model (32B total / 9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Granite 4.0 H Small 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/granite-4-h-small/iphone-17) Sources
- apple.com
- developer.apple.com
- 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/ibm-granite/granite-4.0-h-small
- huggingface.co/ibm-granite/granite-4.0-h-small-GGUF
- layla-network.ai
- macrumors.com
- ollama.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.