text model · Phi-4 · iOS
Can I run Phi-4-reasoning on iPhone Air?
No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
Needs ~10.1 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 2.1 GB: Phi-4-reasoning needs roughly 10.1 GB at Q4_K_M and iPhone Air leaves only about 8 GB usable for a model. The lightest tracked hardware that runs Phi-4-reasoning is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Phi-4-reasoning on Nvidia GeForce RTX 3060 (12GB).
- Q4_K_M needed
- ~10.1 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
- 14B
- Q4_K_M size
- 8.43 GB
- Q8_0 size
- 14.51 GB
- Context
- 32k
- Ollama tag
- phi4-reasoning:14b
- 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 Phi-4-reasoning on other hardware
FAQ
Can iPhone Air run Phi-4-reasoning?
No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
How much memory does Phi-4-reasoning need?
iPhone Air does not have enough memory. At Q4_K_M the weights are ~8.43 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.
What is the best tool to run Phi-4-reasoning 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.
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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.