What is it?
Apple Foundation Models (AFM) is the family of large language models that powers Apple Intelligence. Apple ships two variants: a 3 billion parameter on-device model that runs entirely on the user’s device, and a larger server-based model used for more complex queries via Private Cloud Compute. With iOS 26 / iPadOS 26 / macOS 26, Apple opened the on-device model to third-party developers through the Foundation Models framework — directly callable from Swift, free, and with no per-request cost.
Core specs at a glance
(See spec card above — populated from structured data. Apple has not publicly disclosed the quantized size or context window length, so those fields display as “Not disclosed”.)
What devices can run it?
AFM-on-device requires Apple Intelligence support: iPhone 15 Pro / 15 Pro Max / 16 family on the phone side, iPad with M1 chip or newer, and Mac running Apple silicon. The runtime is the Apple Neural Engine plus Metal acceleration, transparently managed by the OS. Older devices simply do not get Apple Intelligence features. There is no fallback to a smaller model — it is all-or-nothing per device.
Strengths and limitations
Strengths. Zero install — every supported device already has the model. Free for developers via the FoundationModels framework. Tight Swift integration with guided generation, structured output, and tool calling. Excellent privacy story: inference is local, optionally Private Cloud Compute for harder queries with cryptographic verification.
Limitations. Apple-only. Closed weights — you cannot inspect, fine-tune, or self-host. Many spec details (quantization, context length) remain undisclosed by Apple. Cross-platform apps still need a second model for non-Apple devices, doubling QA and content surface area.
When to choose it (and when not to)
Choose AFM-on-device if: your app is exclusive to Apple platforms; you want zero-install AI; you value privacy guarantees backed by Apple’s full-stack control; you want the simplest developer experience for tasks like content tagging, summarization, or structured generation.
Skip it if: you need to ship beyond Apple (Android, Windows, Linux); you need open weights for fine-tuning, distillation, or compliance audits; you need known specs (Gemma 4 publishes everything Apple keeps private).
How it compares to similar on-device models
Closest alternatives are Gemma 4 E2B (2.3B effective, open Apache 2.0, runs anywhere) and Microsoft Phi-4-multimodal (5.6B, MIT-licensed, also adds audio modality). Apple’s strength is the integration story; the open competitors win on portability and inspectability. For a side-by-side, see the leaderboard.
In a real Cove app
Cove Travel and Cove Voice use Gemma 4 across iOS and Android because we need the same model to run on both platforms. AFM-on-device is the model we’d use if Cove were Apple-only — the integration story is unbeatable when your audience is 100% iPhone / iPad. The thinking model behind Cove’s privacy promises (“inference never leaves your device, by architecture”) aligns directly with what Apple Foundation Models stands for.