{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/14"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/8"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/16"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"LiteRT is a runtime for running trained machine learning models on mobile and embedded devices with low latency and minimal binary footprint.","skillfed_tags":["edge-inference","mobile-ml","nightly-build"],"use_cases":["Run trained TensorFlow Lite models for inference on mobile phones and tablets without network latency.","Deploy ML models to embedded systems and IoT devices with constrained memory and CPU.","Build real-time computer vision or audio processing applications that execute locally on-device.","Test and validate model behavior in a nightly development environment before stable release.","Integrate pre-trained models into Android or iOS applications using Python bindings."],"what_it_does":"LiteRT is Google's official runtime for executing machine learning models on mobile and embedded devices. It provides optimized inference with low latency and a small footprint, enabling on-device ML without cloud dependencies. The package wraps a compiled runtime and depends on numpy, protobuf, flatbuffers, and related utilities for tensor manipulation and model loading.\n\nThis is a nightly development build, meaning it receives daily updates and may include experimental features or breaking changes. It targets developers building ML applications for Android, iOS, and other edge platforms who need to run inference directly on the device rather than through a server.","worth_installing":"Yes, if you are actively developing or testing ML inference on mobile/embedded platforms and are comfortable with nightly builds. The package is actively maintained, has no known vulnerabilities, and offers permissive licensing. However, avoid it for production deployments requiring stability\u2014use a stable release instead. The medium install friction is acceptable given the precompiled wheels for common platforms."},"id":"ai-edge-litert-nightly","links":{"html":"https://skillfed.io/packages/ai-edge-litert-nightly","md":"https://skillfed.io/packages/ai-edge-litert-nightly.md","pypi":"https://pypi.org/project/ai-edge-litert-nightly/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":null,"license_treatment":"permissive","name":"ai-edge-litert-nightly","python_support":"unspecified","summary":"LiteRT is for mobile and embedded devices."},"popularity":{"monthly_downloads":184677,"position":10027,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.2.0.dev20260814"}