Google has launched the Gemini Embedding model (gemini-embedding-001), now available to developers via the Gemini API and Vertex AI, showcasing superior performance on the Massive Text Embedding Benchmark. This versatile model supports over 100 languages and features flexible output dimensions, allowing developers to optimize for performance and cost. Users are encouraged to migrate from older models before their deprecation dates, with enhanced features like Batch API support coming soon.

Google has expanded its Gemini AI model family with the launch of Gemini 2.5 Pro and the introduction of the cost-effective Gemini 2.5 Pro Flash-Lite. These models offer significant improvements over previous versions, making them more competitive in the AI landscape, particularly with adjustable thinking budgets for developers. The Flash-Lite variant is designed for high-volume workloads at a fraction of the cost, though it may not be suitable for regular users due to its limitations.

Google has launched the Gemini 2.5 Flash model, offering developers an efficient new tool for building applications with lower API pricing. The rapid release of new models and features in the Gemini app has created a complex selection process for users, as noted by Tulsee Doshi, Google's director of product management for Gemini, who prefers using the more powerful 2.5 Pro version for her work.