Overview
A lightweight Flutter plugin that provides native bindings for ONNX Runtime, enabling efficient inference of machine learning models across Android, iOS, Web, macOS, Windows, and Linux. It allows developers to run ONNX-compatible models directly within Flutter apps, supporting on-device AI processing without relying on cloud services. The plugin is designed for low-latency, high-performance inference with minimal overhead, making it ideal for real-time applications like image recognition, natural language processing, and generative AI tasks. It integrates seamlessly with existing Flutter workflows and supports model loading, tensor manipulation, and execution.
Use cases
- On-device AI inference
- Real-time image and speech processing
- LLM and generative AI in mobile apps
- Cross-platform model deployment
- Offline machine learning applications
Key features
- Supports multiple platforms
- Lightweight native wrappers
- ONNX model execution
- Tensor input/output handling
- Low-latency inference
Suitable for
- Mobile and desktop AI apps
- Developers using ONNX models
- Apps requiring offline AI capabilities
- Performance-sensitive applications
- Cross-platform ML integration
Considerations
- Requires ONNX-compatible models
- Platform-specific setup may be needed
- Limited to ONNX Runtime features
- Model size impacts app bundle
- No built-in model training support