thinkingJack3 · svip

thinkingJack3 is the Thinking Jack embedding model for semantic search, retrieval, clustering, memory, deduplication, recommendation, and RAG indexing. Best for: vector embeddings, document chunk indexing, CRM/contact matching, duplicate detection, semantic memory, search ranking, knowledge-base retrieval, and similarity workflows. Standardized ThinkingJack metadata: - Tier: Embedding / retrieval. - Modality: embedding. - Embedding model. Input limit follows upstream embedding route; max-output-token does not apply.