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Nemotron 3 Nano Omni (free)

Nemotron 3 Nano Omni (free) is NVIDIA’s open multimodal large language model that unifies understanding of video, audio, images, documents, GUIs, and text in a single MoE architecture.

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What is Nemotron 3 Nano Omni (free)?

Nemotron 3 Nano Omni (free) is an open-weight, ~30B-parameter hybrid mixture-of-experts multimodal model from NVIDIA that processes video, audio, images, documents, charts, GUIs, and text with around 3B active parameters per token. It is mainly used to power agentic AI systems that need unified perception and reasoning over long-context multimodal inputs such as document intelligence, video understanding, and audio or screen-based Q&A. It also supports enterprise workflows like summarization, transcription, and multimodal question answering with up to 9x higher throughput than comparable open omni models at similar interactivity levels. It belongs to NVIDIA’s Nemotron 3 family and succeeds earlier Nemotron Nano multimodal models such as Nemotron Nano V2 VL within the broader Nemotron multimodal series.

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Provider Input Output Cache read /M Latency Throughput Uptime
NVIDIA $0.00 $0.00 — ~140ms ~45 tps ~99.9%
AWS Bedrock ~$0.08 ~$0.08 — ~160ms ~40 tps 100.00%
Azure AI ~$0.09 ~$0.09 — ~170ms ~35 tps 100.00%
Google Cloud ~$0.07 ~$0.07 — ~150ms ~50 tps ~99.9%

Try this model

Test Nemotron 3 Nano Omni (free) right here — free to start.

Nemotron 3 Nano Omni (free)
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call the model through the OpenAI-compatible API.

python 
                                        from openai import OpenAI
                                            
                                            client = OpenAI(
                                                api_key="YOUR_API_KEY",
                                                base_url="https://inference.example.com/v1"
                                            )
                                            
                                            response = client.chat.completions.create(
                                                model="nvidia/nemotron-3-nano-omni-free",
                                                messages=[
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ],
                                            )
                                            
                                            print(response.to_json())
                                        
                                    
                                        {
                                                "model": "nvidia/nemotron-3-nano-omni-free",
                                                "messages": [
                                                    {
                                                        "role": "user",
                                                        "content": "Describe this image in one sentence."
                                                    }
                                                ]
                                            }

5 Core Capabilities

  • Conversational Chat

    Engages in multi-turn text conversations, answering questions, following instructions, and maintaining context across user interactions.

  • Code Assistance

    Helps with programming tasks by explaining code, suggesting snippets, and assisting with debugging for common languages and frameworks.

  • Multilingual Translation

    Translates between multiple natural languages, preserving core meaning and providing reasonably fluent outputs for everyday text.

  • Image Interpretation

    Analyzes input images to identify objects and describe visible content, enabling basic visual understanding in context.

  • Text Extraction

    Reads text content from images or screenshots, enabling basic optical character recognition for further processing or understanding.

6 Most Valuable Use Cases

  • On-device chat assistant
  • Code completion helper
  • Summarizing technical articles
  • Productivity email drafting
  • Knowledge base querying
  • Monitoring log explanations

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Unified AI Routing

    Dynamically route each request to the optimal model across providers based on latency, cost, and performance—without changing your integration or redeploying code.

    One endpoint, best model

  • Cost-Aware Orchestration

    Automatically blend premium and budget models using your rules and budgets, so you cut AI spend without manually rewriting prompts or switching providers.

    Control spend, not quality

  • Automatic Fallback Chains

    Recover gracefully from provider outages, timeouts, or rate limits with configurable fallback rules that keep your AI features online and your SLAs intact.

    Stay online by default

  • End-to-End Observability

    Trace every request across models and providers with logs, metrics, and replayable sessions so you can debug regressions and optimize prompts in production.

    See every token, everywhere

  • Task-Level Abstractions

    Describe tasks like chat, extraction, or scoring once and let LLM.API choose the right model and parameters, simplifying complex workflows into a clean API.

    Think tasks, not models

  • High-Throughput Batch

    Process massive workloads efficiently with parallelized, rate-limit-aware batching that maximizes throughput while staying within provider quotas and cost targets.

    Scale jobs, not pain

When to Use — When NOT to Use

Use it if...

  • You need a completely free, lightweight general-purpose model for everyday assistant-style queries.
  • You need a small model suitable for on-device or resource-constrained environments and prototypes.
  • You need inexpensive experimentation with NVIDIA’s ecosystem before committing to larger paid models.
  • Your use case involves simple question-answering, short explanations, or basic writing assistance.
  • Your use case involves low-risk tasks where occasional mistakes are acceptable and easily reviewed.
  • Your use case involves adding basic natural-language features to tools, dashboards, or internal apps.

Avoid if...

  • You need state-of-the-art reasoning, planning, or complex multi-step problem solving for critical workflows.
  • Your workload requires consistently high-quality long-form drafting, editing, and domain-accurate writing.
  • You need strong performance on coding, debugging, or complex software engineering assistance tasks.
  • You need robust handling of long contexts, large documents, or multi-document synthesis and comparison.
  • Your workload requires high factual accuracy and reliability for medical, legal, or financial decisions.
  • You need advanced tools integration, complex function-calling, or sophisticated multi-agent coordination capabilities.

Frequently Asked Questions

  • What is Nemotron 3 Nano Omni (free)?

    Nemotron 3 Nano Omni (free) is an NVIDIA language model accessible via LLM.API, optimized for lightweight, general-purpose text generation and assistance.

  • What is Nemotron 3 Nano Omni (free) best suited for?

    Nemotron 3 Nano Omni (free) is best for fast, low-cost text generation, code assistance, and lightweight reasoning where ultra-low latency matters more than raw capability.

  • How is Nemotron 3 Nano Omni (free) priced on LLM.API?

    Nemotron 3 Nano Omni (free) is offered with zero per-token charges on LLM.API, subject to platform-level free-tier quotas and rate limits.

  • What context window does Nemotron 3 Nano Omni (free) support?

    Nemotron 3 Nano Omni (free) supports a 4K-token context window, suitable for short conversations, prompts, and small documents.

  • How fast is Nemotron 3 Nano Omni (free) on LLM.API?

    Nemotron 3 Nano Omni (free) is optimized for very low latency and high throughput, making it well-suited for real-time and interactive applications.

  • What modalities does Nemotron 3 Nano Omni (free) support?

    Nemotron 3 Nano Omni (free) is a text-only model, accepting text prompts and returning text completions without native image or audio support.

  • How do I access Nemotron 3 Nano Omni (free) through the LLM.API?

    You call the unified LLM.API completion or chat endpoint, specifying the NVIDIA provider and Nemotron 3 Nano Omni (free) as the model identifier.

  • How does Nemotron 3 Nano Omni (free) compare to larger NVIDIA or frontier models?

    Nemotron 3 Nano Omni (free) is smaller and cheaper, trading off complex reasoning and long-context performance for lower latency and resource usage.

  • What limitations should I be aware of when using Nemotron 3 Nano Omni (free)?

    Nemotron 3 Nano Omni (free) may hallucinate, struggle with very long or complex tasks, and is not suitable for mission-critical or highly factual applications.

  • Can I use Nemotron 3 Nano Omni (free) for batch or high-volume workloads?

    Yes, it is well-suited to batch and high-volume workloads, but throughput is governed by LLM.API’s global quotas and rate limits for free models.

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