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APPLE FOUNDATION MODELS · AFM 3

Apple Foundation Models: the AFM 3 family explained

On 8 June 2026 Apple introduced its third generation of foundation models. Two run on-device—AFM 3 Core and the sparse, multimodal AFM 3 Core Advanced—and three run on Private Cloud Compute. Developers reach them through the Foundation Models framework rather than by downloading weights.

How AFM 3 differs from FastVLM and open models

FastVLM, MobileCLIP2 and Depth Pro are open research models you download and run anywhere—browser, Python, MLX. Apple Foundation Models are not distributed as weights: they ship with the operating system and are used through the Foundation Models framework on Apple Intelligence devices. That means zero download for your users and system-level privacy, but also that Apple picks the model and the platform.

Core Advanced: a 20B model that fits in a phone

Apple describes AFM 3 Core Advanced as a sparse architecture whose full weights live in NAND flash. Shared experts stay resident while routed experts are loaded on demand, and an instruction-following pruning scheme lets the model activate only 1–4B parameters per request. The result is a multimodal model with far more capacity than the memory it occupies.

Using the models as a developer

The Foundation Models framework gives you a LanguageModelSession with guided generation into Swift types, tool calling, streaming and—since WWDC26—image input, Dynamic Profiles and a LanguageModel protocol that also accepts Private Cloud Compute, MLX and third-party providers. Python and a CLI are available for scripting and evaluation.

Questions

Can I download AFM 3 weights?

No. Apple Foundation Models are accessed through the framework on supported devices and through Private Cloud Compute. For downloadable Apple models, see FastVLM, MobileCLIP2, Depth Pro, AIMv2 and SHARP.

Which devices run AFM 3 Core Advanced?

Apple ties model availability to Apple Intelligence support and device generation; check SystemLanguageModel availability at runtime instead of assuming a model tier.