Google DeepMind has launched EmbeddingGemma 2, a modular, multimodal model capable of mapping text, images, video, and audio into a single vector space for local device execution.
Perplexity AI has launched two new embedding models, including a 9B parameter version that achieved a 92.4% score on the MADQA benchmark.
Google DeepMind has released EmbeddingGemma 2, a multimodal embedding model built on Gemma 4 that supports text, image, and audio processing with a 8,192-token context window.
Google DeepMind has launched EmbeddingGemma 2, an open-weight multimodal model designed for on-device use with 740 million parameters and commercial-friendly licensing.
Perplexity AI has launched a preview of its new contextual embedding model, pplx-embed-v2-context-9b-preview, designed to improve document retrieval by processing full texts in a single pass.
Linkup Research has launched SPARSEUP, a 149M-parameter sparse embedding model available on Hugging Face under an Apache 2.0 license.
Manticore Search has added native chunking support to its vector search, enabling accurate retrieval from long documents by splitting them into fragments during indexing.
Manticore Search 29.9.0 adds chunked auto-embeddings, mmap access for columnar attributes, and improved support for authenticated backups.
Perplexity has optimized its embedding inference by reusing LLM stack kernels and implementing custom scheduling and graph capture techniques.
