Mirai

Mirai is an Apple SDK and inference engine that optimizes AI models to run locally on iOS and Mac devices. It is built for developers who want to create interactive, ambient, and continuous AI experiences without cloud latency. The platform co-designs models, quantization, and runtime specifically for Apple Silicon, achieving low-latency execution with batch size = 1. By focusing on memory-bound execution and maximizing neural accelerator utilization, Mirai enables applications like real-time parsing, validation, tool calling, and rendering entirely on-device. The lab recently introduced sparse buffers for KV cache to reduce memory usage and a new quantization method that improves speed-quality trade-offs for local LLMs. This is different from traditional on-device approaches because Mirai treats the device as a unique system, not a smaller cloud. Its stack includes local model architectures, a hardware-aware inference engine, advanced quantization, and an application layer for Apple device automation. Mirai offers a macOS app, CLI tool, model conversion, cloud inference option, and a models library with pre-optimized models. It is a specialized tool for Apple developers who demand real-time on-device AI, but it is not a general-purpose solution and requires advanced technical skill.