Why the Frontend Should Run AI Models Locally With ONNX

Running AI models locally in the browser using ONNX Runtime Web offers significant advantages over cloud-based approaches. Local execution eliminates privacy concerns by keeping sensitive data on-device, enables offline functionality, and provides instant feedback loops. ONNX acts as a universal format for ML models, allowing models trained in PyTorch or TensorFlow to run anywhere via JavaScript. Angular's Signals feature (v16+) provides the performance isolation needed for heavy inference operations. The approach enables mixing local models for low-latency tasks with cloud calls for complex reasoning, while maintaining transparency about data handling.