text model · RNJ · iOS
Can I run RNJ-1 8B on iPhone Air?
Yes. RNJ-1 8B runs on iPhone Air at Q4_K_M (~6.3 GB of ~8 GB usable).
Runs at Q4_K_M using ~6.3 GB of ~8 GB usable.
That figure is at a 4k context and moves about ±15% as context length changes. iPhone Air leaves ~1.7 GB of headroom.
- Q4_K_M needed
- ~6.3 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
- 8B
- Q4_K_M size
- 4.76 GB
- Q8_0 size
- 8.23 GB
- Context
- 32k
- Ollama tag
- rnj-1:8b
- 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 RNJ-1 8B on other hardware
FAQ
Can iPhone Air run RNJ-1 8B?
Yes. RNJ-1 8B runs on iPhone Air at Q4_K_M (~6.3 GB of ~8 GB usable).
How much memory does RNJ-1 8B need?
iPhone Air has room to spare. At Q4_K_M the weights are ~4.76 GB; with KV cache and runtime overhead, budget ~6.3 GB at a 4k context.
What is the best tool to run RNJ-1 8B 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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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/rnj-1-8b/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.