text model · Phi-4 · iOS
Can I run Phi-4-mini-reasoning on iPhone Air?
Yes. Phi-4-mini-reasoning runs on iPhone Air at Q4_K_M (~3.6 GB of ~8 GB usable).
Runs at Q4_K_M using ~3.6 GB of ~8 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. iPhone Air leaves ~4.4 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~3.6 GB
- Usable on device
- ~8 GB
- Device memory
- 12 GB
- Best quant
- Q4_K_M
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
- 3.8B
- Q4_K_M size
- 2.32 GB
- Q8_0 size
- 3.8 GB
- Context
- 128k
- Ollama tag
- phi4-mini-reasoning:latest
- Memory
- 12 GB unified
- Usable for weights
- ~8 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
You could also run
Run Phi-4-mini-reasoning on other hardware
FAQ
Can iPhone Air run Phi-4-mini-reasoning?
Yes. Phi-4-mini-reasoning runs on iPhone Air at Q4_K_M (~3.6 GB of ~8 GB usable).
How much memory does Phi-4-mini-reasoning need?
iPhone Air has room to spare. At Q4_K_M the weights are ~2.32 GB; with KV cache and runtime overhead, budget ~3.6 GB at a 4k context.
What is the best tool to run Phi-4-mini-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.