Nemotron-3.5-Embed-1B-BF16 is a compact multimodal embedding model from NVIDIA that maps text, images, and page screenshots into a shared 2048-dimensional vector space for visual document retrieval and semantic search. It pairs the Nemotron-3-Embed-1B text encoder with a vision encoder, supports up to 32k tokens and Matryoshka dimensions, and suits multilingual RAG over PDFs, slides, and scanned documents.
$0.0075
Share of requests served without a server error. Client errors (4xx) do not count.
No optional parameters beyond the standard request.
Works with the OpenAI SDK pointed at our base URL. Every parameter is in the API reference.
Tokens embedded per day on NagaAI.
Nemotron-3.5-Embed-1B-BF16 is a compact multimodal embedding model from NVIDIA that maps text, images, and page screenshots into a shared 2048-dimensional vector space for visual document retrieval and semantic search.
On NagaAI, Nemotron 3.5 Embed 1B costs $0.0075 per 1M tokens. You pay only for what you use, with no subscription.
It takes text as input and returns embeddings.
Create an API key, copy the model ID from the top of this page and send requests with the OpenAI SDK pointed at NagaAI. The API section on this page has a ready example.
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