Is Llama Nemotron Rerank VL 1B V2 (free) free?

Yes. The pricing shown on this page for Llama Nemotron Rerank VL 1B V2 (free) is zero, so you are not charged for ranked documents. Free endpoints are rate limited — see the rate limit docs.

How much text can Llama Nemotron Rerank VL 1B V2 (free) process at once?

Llama Nemotron Rerank VL 1B V2 (free) accepts up to 10,240 tokens per query and document. Longer text has to be split into multiple documents.

What inputs and outputs does Llama Nemotron Rerank VL 1B V2 (free) support?

Llama Nemotron Rerank VL 1B V2 (free) accepts text and images as input and returns relevance-ranked documents.

Which providers serve Llama Nemotron Rerank VL 1B V2 (free)?

Llama Nemotron Rerank VL 1B V2 (free) is served by 1 provider on OpenRouter: NVIDIA.

What other reranking models does Nvidia have?

Nemotron 3.5 Rerank 8B (free) is another reranking model from Nvidia.

When was Llama Nemotron Rerank VL 1B V2 (free) released?

Llama Nemotron Rerank VL 1B V2 (free) was released on June 9, 2026.

For the free endpoint, please do not upload any confidential information or personal data (such as voices or faces of people). Your use is logged for security purposes and to improve NVIDIA products and services. The logged session data for improvement purposes is not linked to your identity or any persistent identifier. For more information about NVIDIA's data processing practices, see Privacy Policy. By using this free endpoint, you consent to NVIDIA's collection, recording, and use of such information and the NVIDIA API Trial Terms of Service

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

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

Llama Nemotron Rerank VL 1B V2 is a 1.7B multimodal reranking model from NVIDIA. It evaluates the relevance of document images and text against user queries, designed for vision RAG pipelines handling charts, tables, infographics, and mixed-media documents. Functions as a cross-encoder that accepts text queries paired with image, text, or combined document inputs, delivering approximately 6-7% recall improvements over embedding-only baselines on visual document retrieval benchmarks.

Modalities

Price

Free

Context

10K

Released

Jun 9, 2026

Providers

This model is hosted by one provider. OpenRouter forwards every request without routing.

Latency


	Free	Free	0.86s	100.00%

Input FreeOutput Free
0.86s latency100.00% uptime

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.95%

Availability over the last 3 days

Last 72 hours

Availability 99.95%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.94%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Not currently available through EU in-region routing. In-region routing docs

More models from Nvidia

Nemotron 3.5 Transcribe

Nemotron 3.5 Transcribe is an open-weight speech recognition model from NVIDIA, a 30B mixture-of-experts with about 4B active parameters. It transcribes recordings of up to one hour in 40 languages, with speaker attribution, speech translation, and prompt-guided vocabulary and style.

Transcription$0.000017/second

Nemotron 3.5 Embed 1B (free)

Nemotron 3.5 Embed 1B is a multimodal embedding model from NVIDIA for multilingual retrieval over text and document page images (tables, charts, infographics). Queries are text and documents can be text, an image, or both. It returns 2048-dim vectors that can be truncated, and shares the text embedding space of Nemotron 3 Embed 1B.

EmbeddingsFree

Nemotron 3.5 Embed 8B (free)

Nemotron 3.5 Embed 8B is a multimodal embedding model from NVIDIA for multilingual retrieval over text and document page images (tables, charts, infographics). Queries are text and documents can be text, an image, or both. It returns 4096-dim vectors that can be truncated, and shares the text embedding space of Nemotron 3 Embed 8B.

EmbeddingsFree

Nemotron 3.5 Rerank 8B (free)

RerankFree

Nemotron 3.5 Super VL

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video as input and returns text, and is built for long-running agents that combine visual understanding with reasoning and tool use.

It uses a hybrid Mamba-Transformer architecture with multi-token prediction and supports a 1M-token context. Typical uses include document intelligence, web research, coding validation, customer service, and video understanding. Reasoning is on by default and can be turned off or given a token budget.

Text1.0M context$0.06 / $0.35

Nemotron 3.5 Super VL (free)

Text1M contextFree

Switchyard

Switchyard is an open-source model routing system that switches between multiple models to optimize the cost of requests. By default it will use OpenRouter market data to select the most popular low and high cost models. You can pass in two choices in the models parameter as well as specify any of the routing algorithms Switchyard offers. Details in the Switchyard docs. OpenRouter then applies its normal provider routing, fallbacks and billing for the chosen model.

Text1M context

Nemotron 3.5 ASR Streaming Multilingual 0.6B

Nemotron 3.5 ASR Streaming Multilingual 0.6B is a speech recognition model from NVIDIA. Its prompt-conditioned, cache-aware FastConformer-RNNT design targets low-latency transcription across more than 40 languages for real-time captioning, voice agents, and multilingual transcription pipelines.

Transcription$0.000003/second

Nemotron 3.5 Lightning

NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that benefit from domain-specific customization.

Text262K context$0.025 / $0.12

Nemotron 3.5 Lightning (free)

Text1M contextFree

Nemotron 3 Embed 1B (free)

NVIDIA Nemotron 3 Embed 1B is an open text embedding model from NVIDIA, optimized for high-throughput, low-latency retrieval. It is suited for enterprise search, RAG, code retrieval, and agentic retrieval workflows, retaining more than 95% of the 8B model’s accuracy in a smaller deployment footprint.

EmbeddingsFree

Llama Nemotron Rerank VL 1B V2 (free)

RerankFree

Nemotron 3.5 Content Safety

NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting text and image input and returning text output: a safe/unsafe classification for the user prompt and the response, safety category labels, and an optional reasoning trace. It covers 12 languages with a context window of up to 128K tokens.

It is suited for prompt and response moderation, content classification, safety pipelines, and enterprise AI guardrails with policy enforcement, and includes a togglable reasoning mode. It is part of the NVIDIA Nemotron family of open models for agentic AI.

Text131K context$0.20 / $0.20

Nemotron 3 Ultra

NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it supports text input and output with a context window of up to 1M tokens. It is suited for long-running agentic workflows, including agent orchestration, coding agents, deep research, and complex enterprise tasks.

It is particularly strong at multi-step reasoning and planning, with high-throughput inference designed for high-volume agent pipelines. It is part of the NVIDIA Nemotron family of open models for agentic AI.

Text262K context$0.50 / $2.20

Nemotron 3 Ultra (free)

Text1M contextFree

Parakeet TDT 0.6B v3

Parakeet TDT 0.6B v3 is NVIDIA's 600M-parameter multilingual speech-to-text model built on the FastConformer-TDT architecture. Trained on the Granary dataset (670,000+ hours of audio), it supports automatic language detection across all official EU languages and achieves a 6.34% average word error rate on the HuggingFace Open ASR Leaderboard. Returns transcribed text with punctuation and segment timestamps.

Transcription$0.000017/second

Nemotron 3 Nano Omni (free)

NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and audio inputs and produces text output, enabling agents to perceive and reason across modalities in a single inference loop.

Built on a hybrid MoE Transformer-Mamba architecture with Conv3D video layers and Efficient Video Sampling (EVS), it delivers approximately 2× higher throughput and 2.5× lower compute for video reasoning versus separate vision + speech pipelines. It supports up to 300K context length and a 16,384 reasoning budget, with extended thinking enabled via reasoning.enabled on OpenRouter.

Text256K contextFree

Nemotron 3 Super

NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer Mixture-of-Experts architecture with multi-token prediction (MTP), it delivers over 50% higher token generation compared to leading open models.

The model features a 1M token context window for long-term agent coherence, cross-document reasoning, and multi-step task planning. Latent MoE enables calling 4 experts for the inference cost of only one, improving intelligence and generalization. Multi-environment RL training across 10+ environments delivers leading accuracy on benchmarks including AIME 2025, TerminalBench, and SWE-Bench Verified.

Fully open with weights, datasets, and recipes under the NVIDIA Open License, Nemotron 3 Super allows easy customization and secure deployment anywhere — from workstation to cloud.

Text262K context$0.075 / $0.40

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.

EmbeddingsFree

Nemotron 3 Nano 30B A3B

NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems.

The model is fully open with open-weights, datasets and recipes so developers can easily customize, optimize, and deploy the model on their infrastructure for maximum privacy and security.

Text262K context$0.06 / $0.24

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

Providers

Performance

Uptime

Availability over the last 3 days

Availability over the last 24 hours

Apps

Activity

API

Frequently asked questions

Explore more models

More models from Nvidia

More models from Nvidia

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

Providers

Performance

Uptime

Availability over the last 3 days

Availability over the last 24 hours

Apps

Activity

API

Frequently asked questions

What is Llama Nemotron Rerank VL 1B V2 (free)?

Is Llama Nemotron Rerank VL 1B V2 (free) free?

How much text can Llama Nemotron Rerank VL 1B V2 (free) process at once?

What inputs and outputs does Llama Nemotron Rerank VL 1B V2 (free) support?

Which providers serve Llama Nemotron Rerank VL 1B V2 (free)?

What other reranking models does Nvidia have?

When was Llama Nemotron Rerank VL 1B V2 (free) released?

Explore more models

More models from Nvidia

More models from Nvidia