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NVIDIA: Llama Nemotron Embed VL 1B V2 (free)

nvidia/llama-nemotron-embed-vl-1b-v2:free

The Llama Nemotron Embed VL 1B V2 embedding model is optimized for multimodal question-answering retrieval. The model can embed 'documents' in the form of image, text, or image and text combined. Documents can be retrieved given a user query in text form. The model supports images containing text, tables, charts, and infographics.

Modalities

In / Out Price

$0 / $0per 1M

Context

131K

Weekly Rank

#187on OpenRouter

Overview
Providers
Performance
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Activity
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API

Performance for Llama Nemotron Embed VL 1B V2 (free)

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Effective Pricing for Llama Nemotron Embed VL 1B V2 (free)

Actual cost per million tokens across providers over the past hour

Apps using Llama Nemotron Embed VL 1B V2 (free)

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Uptime stats for Llama Nemotron Embed VL 1B V2 (free)

Uptime stats for Llama Nemotron Embed VL 1B V2 (free) across all providers

Providers for Llama Nemotron Embed VL 1B V2 (free)

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Sample code and API for Llama Nemotron Embed VL 1B V2 (free)

OpenRouter normalizes requests and responses across providers for you.

OpenRouter supports image input embeddings for models that can generate embeddings from both text and images. Pass multimodal content using the content array format with text and image_url components. Learn more about image embeddings.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.