INSIDE’s brief compatibility note says Apple Intelligence support is almost equivalent to Siri AI support. However, it highlights an exception: some features need a more advanced on-device model. Those higher-end Siri AI capabilities currently support only iPhone 17 Pro, iPhone 17 Pro Max, and iPhone Air.
Apple announced CoreAI at WWDC, which the post frames as a possible future replacement for CoreML and an alternative to MLX, llama.cpp, and torch for optimized on-device inference. Models still need conversion through Python scripts, and current supported models appear mostly from mid-2025. No performance data is available yet; the author expects it may trail MLX on GPU, but Apple’s 20B on-device foundation model claim suggests larger app-bundled models could become possible.
Simon Willison says Apple’s 2024 Apple Intelligence rollout made him cautious, so he will believe the WWDC 2026 Siri AI claims only after seeing results. He notes the new features look more feasible, especially with a custom Gemini-derived model running on Private Cloud Compute. He also highlights vision LLM screen understanding and the new Core AI library for running PyTorch-derived models on Apple hardware.
Apple’s Core AI framework is positioned as a developer stack for deploying AI models directly inside apps on Apple silicon. The documentation describes Swift APIs, `.aimodel` assets, model specialization, caching, Xcode profiling, and debugging tools. It appears aimed at developers building low-latency, privacy-conscious on-device inference workflows, though the documentation is marked as preliminary beta information.
Ars Technica reports that Apple is working to compress Google’s massive Gemini model so it can run on iPhone and power a new Siri experience. The short summary emphasizes a key constraint: even with on-device ambitions, a cloud component is probably inevitable. Details remain limited, so the report is best read as a signal about Apple’s AI direction rather than a confirmed product launch.