Gemini Embedding now generally available in the Gemini API- Google Developers Blog

Announces the general availability of the `gemini-embedding-001` text model in the Gemini API and Vertex AI. Highlights its top performance on the MTEB Multilingual leaderboard, its versatility across domains, and its technical details including multi-language support (100+ languages), 2048 token input length, and Matryoshka Representation Learning (MRL) for scalable output dimensions. Details pricing ($0.15 per 1M input tokens) and rate limits, with free and paid tiers available. Provides a Python code example for using the `embed_content` endpoint and links to documentation and quickstart notebooks. Notifies developers about the deprecation of experimental and legacy embedding models.