TensorFlow Lite for Microcontrollers is designed to run deep learning models on bare-metal systems, DSPs, and microcontrollers with limited memory (tens to hundreds of kilobytes). It runs models converted via LiteRT and TensorFlow.
- Tier-1 Architectures (Tested in CI): Arm Cortex-M (CMSIS-NN / Corstone), Cadence Xtensa (HiFi 3/4/5, Vision P6), RISC-V, Qualcomm Hexagon, and x86/Windows.
- Community Platforms & SDKs: Arduino, Coral Dev Board Micro, Espressif ESP32, Renesas, Silicon Labs, and Ingenic MIPS.
- Core Concepts:
- Porting & Hardware Optimization:
- Tooling, Compression & Python:
- Questions & Issues: Please file a GitHub Issue.
- Contributing: Review our Contributing Guide.
- Security: Report vulnerabilities according to our Security Policy.