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Chroma has released Context-1, a 20B parameter Mixture of Experts model trained specifically for retrieval tasks that require multi-hop reasoning. The model decomposes complex queries into subqueries, performs parallel tool calls, and actively prunes its own context mid-search—achieving comparable performance to frontier models at a fraction of the cost and up to 10x faster inference speed.

Perplexity has open-sourced two text embedding models designed to match or exceed the performance of Google's and Alibaba's embeddings while requiring significantly less memory. The move brings competitive embedding technology into the open-source ecosystem.