If you've ever wanted AI in your Flutter app without Gemini API costs, this is it.

Hey guys! It's Samuel once again. Today, we're going to be integrating something cool: On-device AI: no cloud, no internet - just pure privacy and speed with TensorFlow Lite. We will use TensorFlow Lite to build an image classifier that recognizes objects in real-time from your camera or gallery.

Why on-device in 2026? Cloud AI is great, but on-device wins for offline apps, privacy (no data sent), and battery life. Flutter's ecosystem is mature. We have tflite_flutter that handles delegates beautifully now.

We'll use MobileNet (quantized for mobile), download the .tflite model and labels.txt from TensorFlow Hub.

New project: flutter create ai_classifier .

Create a new assets folder in your project directory: assets/models, and download the mobilenet file and labels.text file and place it inside the assets/models folder.

Next, install dependencies in pubspec.yaml:

dependencies : flutter_riverpod : ^3.2.0 google_fonts :…