Long context is where iPhone-local AI hits its hardest wall: the ~5.6GB budget barely covers a small model plus a few thousand tokens of cache. Useful for an article or an email thread, but not for documents plural.
Granite / 3B / Q4_K_M / ~2 GB
Best for: Lightweight chat, classification, edge tasks·Pop: 56/100
Perf: ~24.0 tok/s · first token ~0.9s
Best for lightweight chat, classification, edge tasks. Strong fit for 8 GB RAM with balanced speed and quality.
LFM2 / 8.3B / Q4_K_M / ~5.5 GB
Best for: On-device agents, tool calling, multilingual chat·Pop: 72/100
Perf: ~7.7 tok/s · first token ~1.8s
This model may feel memory-heavy on 8 GB RAM, but it is still listed for balanced speed and quality.
Granite / 8B / Q4_K_M / ~5.5 GB
Best for: Enterprise assistant, tool calling, instruction following·Pop: 62/100
Perf: ~7.9 tok/s · first token ~1.7s
This model may feel memory-heavy on 8 GB RAM, but it is still listed for balanced speed and quality.
With a 2B-4B model loaded, the remaining memory supports windows in the 4K-8K range: a long article, a meeting transcript, an email chain. Push further and the app either truncates silently or slows to a crawl; phone AI apps rarely surface which, so test with a known-length document.
The workable mobile pattern is summarize-and-carry: condense on the phone, accumulate summaries in notes, do corpus-scale questions on a Mac later. For genuine document analysis from your pocket, remote-control a home Mac (Tailscale plus Open WebUI) instead of fighting the phone.
Use the ModelFit wizard to test different RAM and chip configurations for your exact iPhone 16 Pro setup.
Open ModelFit Wizard