Original sourceGoogle Developers Blog
Summary
Google announced the LiteRT Tensor API for authoring and optimizing on-device AI models, providing native C++ and shader-level control, portable across CPU, GPU (ML Drift) and NPU. Developers can build computation graphs operator by operator, precisely choosing operations and connections, while ret…
Key points
- For teams needing to squeeze performance on specific hardware or do agent-driven automatic graph tuning, this offers a finer control layer than standard conversion paths.
- Edge inference performance depends on precise control of computation graphs and memory movement; low-level APIs determine the achievable ceiling.
- Developers can start with standard conversion paths, then switch to the Tensor API for end-to-end accelerator execution and graph reconstruction when hitting performance bottlenecks.
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