NV
NVIDIA: Llama Nemotron Embed VL 1B V2
Free allowance
Up to50requests / day
via OpenRouter · < $10 credits
- 20 requests / minute
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...
- Input
- text
- image
- Output
- embeddings
Providers
Available through 1 free provider. Use the model ID and API settings below to connect.
* The provider match may differ from this model. Check its docs for details.
Benchmarks
Compare scores and explore results by category.
No benchmark results are available for this model yet.
Frequently asked questions
Free access, setup, and what to expect.
Llama Nemotron Embed VL 1B V2 is available with up to 50 requests / day free through OpenRouter (< $10 credits). Additional limits apply at the same time: 20 requests / minute. Free allowances can change. Check the Llama Nemotron Embed VL 1B V2 provider limits before you start.
To use Llama Nemotron Embed VL 1B V2, choose one of the listed Llama Nemotron Embed VL 1B V2 API providers and follow the provider’s account and API-key setup guide. Copy the Llama Nemotron Embed VL 1B V2 model ID and connection settings for your chosen provider into your app or API client. Model IDs can differ between providers. API requests go directly to the provider; Free Models is a comparison site.
Llama Nemotron Embed VL 1B V2 accepts text and image as listed input formats. Listed output formats include embeddings. Image or audio input support does not imply image or audio generation. Check the chosen provider’s Llama Nemotron Embed VL 1B V2 documentation for supported file types and request formats.
Llama Nemotron Embed VL 1B V2 has a listed context window of 131K tokens. Tokens are small pieces of content rather than a word count. Instructions, conversation history, and other inputs use context space, and the response also needs room. The maximum output length for Llama Nemotron Embed VL 1B V2 may be smaller than the context window and can vary by provider.
Neither reasoning nor tool calling support is listed for Llama Nemotron Embed VL 1B V2. Reasoning enables additional processing for complex problems. Tool calling allows a model to request functions that your app executes. Check the chosen provider’s documentation for capability availability and setup.
No benchmark results are listed for Llama Nemotron Embed VL 1B V2 yet. Missing scores don’t establish poor performance. Compare scores within the same benchmark: coding indexes, Elo ratings, and win rates measure different things. The index comparison charts include only scored free models listed on Free Models. Evaluate Llama Nemotron Embed VL 1B V2 on examples from your own task alongside context size and provider limits.