Meet the LiteRT Tensor API: giving developers native C++ control over the model graph to unify end-to-end ML computations on heterogeneous edge hardware.
Read the original at Google AI developers blog: Native Model Authoring for Edge with LiteRT Tensor API
How OpenSmartRoute helps
The router treats agents, tools and skills as targets in the same catalogue as models. An MCP tool or an A2A agent is one entry; the router picks it when it fits the request and learns from how it performs. The same guard and resource limits apply to a tool's arguments as to a prompt.
For a team that routes through the router, a release like this is one catalogue entry. The new model competes on the next request against what the team already runs, on quality, cost and speed. If it answers well it earns more traffic; if it fails it gets less, with no code change in the app.
Source: https://developers.googleblog.com/native-model-authoring-for-edge-with-litert-tensor-api/