AI Models for iPhone 18 Pro Max — What runs on 12GB

47 great · 5 slow · 57 won't fit
Chip
Apple A20 Pro
Memory bandwidth
115.2 GB/s
NPU
—
RAM options
12 GB
Usable for models
~7.8 GB
Year
2026

Specs checked against manufacturer and public documentation on .

What runs on the iPhone 18 Pro Max

All 109 models at their recommended quant, on the 12GB configuration. Select any row for the full report.

ModelParamsQuantNeedsSpeedVerdict

~ = bandwidth-based estimate · ✓ = measured on real hardware

Best model by use case

Best for Chat

Top everyday assistant & writing pick here — ~86.4 tokens/s at Q8_0, using 1.3 of ~7.8GB.

Best for Coding

Top code completion & explain-this pick here — ~20.7 tokens/s at Q4_K_M, using 3.5 of ~7.8GB.

Best for Reasoning

Top math & step-by-step thinking pick here — ~20.7 tokens/s at Q4_K_M, using 3.5 of ~7.8GB.

FAQ

What is the biggest AI model the iPhone 18 Pro Max can run?

Bonsai 27B (1-bit) (27B parameters) at Q1_0 — it needs 4.8GB of the ~7.8GB usable on the 12GB iPhone 18 Pro Max and runs at ~13.6 tokens/s.

How much of the iPhone 18 Pro Max's 12GB RAM can AI models actually use?

About 7.8GB. iOS caps a single app at roughly 65% of total RAM, so of the 12GB about 7.8GB is actually available to a model.

Can the iPhone 18 Pro Max run Llama 3.1 8B?

Yes — at Q4_K_M it needs 6.3GB of the ~7.8GB usable and runs at ~10.6 tokens/s.

How fast is local AI on the iPhone 18 Pro Max?

The Apple A20 Pro has 115.2GB/s of memory bandwidth, which is what decode speed scales with. Small models like Ternary Bonsai 1.7B reach ~103.7 tokens/s; larger 7–14B models land in the single digits. Anything above ~8 tokens/s feels smooth for chat.

Which quantization should I use on the iPhone 18 Pro Max?

Q4_K_M is the size/quality sweet spot for most models. For example, Qwen3 0.6B at Q8_0 takes 1.3GB of memory here. Only drop to Q3 or IQ4 if a model just misses fitting; Q8 rarely pays off on 12GB of RAM.

Is 12GB of RAM enough for local AI?

52 of the 109 models we track fit on the iPhone 18 Pro Max — 47 run great and 5 run with compromises. 57 models (mostly 12B+) don't fit at their recommended quant.

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