• 28 January 2026 How Automated Prompt Optimization Unlocks Quality Gains for ML Kit’s GenAI Prompt API Posted by Chetan Tekur, PM at AI Innovation and Research, Chao Zhao, SWE at AI Innovation and Research, Paul Zhou, Prompt Quality Lead at GCP Cloud AI and Industry Solutions, and Caren Chang, Developer Relations Engineer at Android Automated Prompt Optimization (APO) To further help bring your ML Kit Prompt API use cases to production, we are excited to announceAutomated Prompt Optimization (APO) targeting On-Device models on Vertex AI. • Automated Prompt Optimization is a tool that helps you automatically find the optimal prompt for your use cases. • The era of On-Device AI is no longer a promise-it is a production reality. • With the release ofGemini Nano v3, we are placing unprecedented language understanding and multimodal capabilities directly into the palms of users. • Through the Gemini Nano family of models, we have wide coverage of supported devices across the Android Ecosystem. • But for developers building the next generation of intelligent apps, access to a powerful model is only step one.
Article Summaries:
- Google announced Automated Prompt Optimization (APO) for its ML Kit GenAI Prompt API, a tool that automatically refines prompts for on‑device models on Vertex AI. APO uses server‑side models (Gemini Pro, Flash) to generate, evaluate, and select optimal prompts, employing automated error analysis, semantic instruction distillation, and parallel candidate testing. The feature is designed to match the performance of fine‑tuning while staying within Android’s memory‑efficient AICore architecture. APO works with Gemini Nano v3, the production‑ready version of Gemma 3N, enabling developers to tailor foundation models for specific use cases without deploying custom LoRA adapters.
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