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.

Llama 4 Maverick is a state-of-the-art multilingual model designed for image and text understanding, creative writing, and enterprise applications. While it is not yet supported on Together AI, users can register for an account to access various API functionalities, including image generation, chat completions, and audio transcriptions. The model allows for versatile applications such as generating videos and embeddings based on user prompts.

Qwen-MT has been updated to enhance its multilingual understanding and translation capabilities, supporting 92 languages with high accuracy and fluency. The model incorporates reinforcement learning and offers customizable features for specialized translation needs, while achieving low latency and cost efficiency. Evaluation results demonstrate superior performance over comparable models, with robust support for various contexts and terminologies.