Google AI Edge Gallery – AI applications launched by Google that support running AI models offline on mobile devices

What is Google AI Edge Gallery？

Google AI Edge Gallery is an experimental application launched by Google that allows users to experience and use Machine Learning (ML) and Generative AI (GenAI) models on local devices. The application currently supports running on Android devices and can be used without an internet connection. Users can switch between different models to perform image question answering, text generation, multi-turn conversations, and view performance metrics in real time. The app supports testing with built-in models and provides rich resources and tools for developers to explore the powerful capabilities of on-device AI.

Main Features of Google AI Edge Gallery

• Local offline operation: No internet connection required; all processing is done on the device.

• Model selection: Easily switch between different models from Hugging Face and compare their performance.

• Image question answering: Upload an image to ask questions, get descriptions, solve problems, or identify objects.

• Prompt Lab: Summarize, rewrite, generate code, or explore single-turn LLM use cases with free-form prompts.

• AI chat: Conduct multi-turn conversations.

• Performance insights: Real-time benchmarking (first response time, decoding speed, latency).

• Built-in models: Test local LiteRT .task models.

• Developer resources: Quick links to model cards and source code.

Technical Principles of Google AI Edge Gallery

• Google AI Edge: Google AI Edge is the core framework for on-device machine learning, providing a suite of APIs and tools to efficiently run ML models on mobile devices.

• LiteRT: A lightweight runtime environment designed to optimize model execution efficiency. Based on efficient memory management and computational optimization, it ensures fast model execution on mobile devices while minimizing resource consumption. LiteRT supports multiple model formats, including but not limited to TensorFlow Lite and ONNX.

• LLM Inference API: An interface that supports the inference of large language models (LLMs) on devices. It enables applications to run complex language models like GPT or other Transformer-based models locally without relying on cloud services.

• Hugging Face Integration: Integrated with Hugging Face’s model hub, allowing users to easily discover and download various pre-trained models. Hugging Face provides a rich set of models across domains such as natural language processing and computer vision. With this integration, users can directly use models in the Gallery without manual downloading or configuration.

Project Link of Google AI Edge Gallery

• GitHub Repository: https://github.com/google-ai-edge/gallery

Application Scenarios of Google AI Edge Gallery

• Personal entertainment and creativity: Users can upload images for Q&A, generate creative texts, or engage in multi-turn conversations with AI to meet entertainment and creative needs.

• Education and learning: Acts as a tool to assist with language learning, science experiments, and programming education, enhancing learning effectiveness.

• Professional development and research: Developers can test and optimize models, rapidly build prototypes, and compare the performance of different models to support the development process.

• Enterprise and business: Enterprises can develop localized customer support tools, and technicians can solve problems in offline environments while ensuring data privacy.

• Daily life: Assists with travel planning, smart home control, and health advice, enhancing everyday convenience.