Unverified50% confidenceFactExact time
nomic-embed-text is an open-source text embedding model released by Nomic that can run locally, converting text into vectors for semantic search.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Managing 900+ Obsidian Notes with a Knowledge Graph
rss10/19/2026
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Related Claims
Unverifiednomic-embed-text is an open-source text embedding model released by Nomic AI, designed specifically for RAG scenarios; it encodes text chunks into 768-dimensional vectors and supports a context window of up to 8,192 tokens.75% similarVerifiednomic-embed-text is an open-source embedding model that supports long-context input of up to 8,192 tokens73% similarUnverifiedThe text encoder is responsible for converting prompt strings into vector representations (conditioning) that the model can read, and serves as the core bridge connecting textual descriptions to image generation68% similarUnverifiedText embedding technology has followed a development path from Word2Vec and Sentence-BERT to general-purpose embedding models based on instruction fine-tuning.68% similarUnverifiedThe language model receives a single flat stream of text containing the system prompt, user messages, retrieved documents and tool return results, with no reliable way to distinguish instructions from ordinary content.67% similar
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