text model · OpenELM · iOS
Can I run Apple OpenELM 3B on iPhone 17 Pro?
Yes. Apple OpenELM 3B runs on iPhone 17 Pro at Q4_K_M (~3 GB of ~8 GB usable).
Runs at Q4_K_M using ~3 GB of ~8 GB usable. You have room for FP16 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. iPhone 17 Pro leaves ~5 GB of headroom, room to step up to FP16 for higher quality.
- Q4_K_M needed
- ~3 GB
- Usable on device
- ~8 GB
- Device memory
- 12 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~12 W
- Electricity / 1M tokens
- ~$0.02
- Pays for itself after
- ~2,290M tok
At ~$0.15/kWh and the estimated ~22 tok/s, a million generated tokens costs about $0.02 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,099 iPhone 17 Pro pays for itself after roughly 2,290 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 3B
- Q4_K_M size
- 1.76 GB
- Q8_0 size
- 3.01 GB
- Context
- 2k
- Memory
- 12 GB unified
- Usable for weights
- ~8 GB
- Power draw
- ~12 W
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
You could also run
Run Apple OpenELM 3B on other hardware
FAQ
Can iPhone 17 Pro run Apple OpenELM 3B?
Yes. Apple OpenELM 3B runs on iPhone 17 Pro at Q4_K_M (~3 GB of ~8 GB usable).
How much memory does Apple OpenELM 3B need?
iPhone 17 Pro has room to spare. At Q4_K_M the weights are ~1.76 GB; with KV cache and runtime overhead, budget ~3 GB at a 4k context.
What is the best tool to run Apple OpenELM 3B 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.