Google LiteRT
A machine learning inference framework from Google for mobile and edge devices, supporting efficient model execution on CPU, GPU and NPU along with a quantization toolchain.
Timeline (last 90 days)
All of Pipit's processing is done on the phone's chip via a quantized Google LiteRT multimodal model, and the app can run fully air-gapped, emphasizing zero cloud and zero tracking.
The actual performance of the 50ms latency claim depends heavily on whether the device supports the corresponding delegation backend, whether the model operators are fully covered, and the size of the index.
Pipit relies heavily on Google's ML Kit and LiteRT ecosystem, and its model size and hardware acceleration capabilities are limited by the support scope of Google's toolchain.
Google LiteRT (formerly TensorFlow Lite) provides toolchains such as post-training quantization and quantization-aware training, and supports execution on CPU, GPU and NPU.
All Facts (4)
All of Pipit's processing is done on the phone's chip via a quantized Google LiteRT multimodal model, and the app can run fully air-gapped, emphasizing zero cloud and zero tracking.
50%UnverifiedThe actual performance of the 50ms latency claim depends heavily on whether the device supports the corresponding delegation backend, whether the model operators are fully covered, and the size of the index.
50%UnverifiedPipit relies heavily on Google's ML Kit and LiteRT ecosystem, and its model size and hardware acceleration capabilities are limited by the support scope of Google's toolchain.
50%UnverifiedGoogle LiteRT (formerly TensorFlow Lite) provides toolchains such as post-training quantization and quantization-aware training, and supports execution on CPU, GPU and NPU.
50%