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Nemotron 3 Embed 1BFree

NVIDIA
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NVIDIA Nemotron-3-Embed-1B is a 1.14B-parameter multilingual text embedding model (2048 dimensions, 34 languages) for semantic search, retrieval, and RAG. Built on Ministral-3-3B-Instruct; state-of-the-art on multilingual retrieval benchmarks (MMTEB 71.05, RTEB 72.38). Served via NVIDIA NIM.

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NVIDIA
nvidia
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NVIDIA
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API & code

Embeddings API

/api/v1/embeddings

Generate embedding vectors for search, RAG, and clustering.

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Embedding vectors
Vector dimensionsNot published
Max input32,768 tokens
PriceFree on AnyRouter
Request parameters
inputmodelencoding_format
ArchitectureTransformer
Categoryembedding
ReleasedJul 16, 2026
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Capabilities
Embeddings are fixed-length vectors — compare them with cosine similarity for semantic search, RAG retrieval, clustering, and deduplication. Embed queries and documents with the same model, or the distances are meaningless.
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