Apple announced new on device inference engine for Apple Silicon

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Summary

Apple announced CoreAI, a new on-device inference engine for Apple Silicon at WWDC, replacing CoreML and supporting larger models up to 20B parameters via optimized inference, with a focus on phones and tablets.

This news seem to have flown under the radar. Apple announced CoreAI on WWDC which is basically a future replacement for CoreML and an alternative to MLX/llama.cpp/torch for on-device optimized inference, especially on phones and tablets. The model weights need to be converted similarly to CoreML via python script, atm the list of supported models is mostly from mid 2025 year though [https://github.com/apple/coreai-models/tree/main/models](https://github.com/apple/coreai-models/tree/main/models) . For anyone wondering how is that anything new - CoreML out of the box didn't even support models beyond a few billion params and had very limited supported operations pool. This implies big update to ANE ops too. There's nothing on performance yet, it is very likely that it's inferior to pure MLX on GPU atm. The only other interesting thing is that they boast 20B model to be deployed on device for foundation models [https://machinelearning.apple.com/research/introducing-third-generation-of-apple-foundation-models](https://machinelearning.apple.com/research/introducing-third-generation-of-apple-foundation-models), which looks to be lazily loaded MoE, so perhaps CoreAI will allow to deploy larger models with apps as well.
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