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NVIDIA Nemotron 3 Nano Omni Vision

nvidia /

NVIDIA Nemotron 3 Nano Omni is an open, efficient reasoning model for enterprise agentic workflows, built on a 30B A3B hybrid Transformer-Mamba MoE architecture. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-text
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If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.

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{
  "output": "This is a black and white photograph capturing a bustling city street scene, likely from the mid-20th century. The image is taken from an elevated perspective, looking down a wide, straight road that recedes into the distance.\n\nThe street is filled with numerous vintage automobiles, characteristic of the 1940s or 1950s, including sedans and a few convertibles. The cars are in motion and parked along both sides of the road. On the left side, a building with a sign that appears to read \"COSCO\" is visible, and a crowd of pedestrians can be seen on the sidewalk. On the right, a prominent corner building with a clock on its facade stands out. The overall atmosphere is one of a busy, active urban environment."
}

$0.006每次運行·~166 / $1

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相關模型

README

NVIDIA Nemotron-3 Nano Omni Vision

NVIDIA Nemotron-3 Nano Omni Vision is a multimodal vision-language model for image understanding and analysis. Upload an image, provide an English prompt, and the model generates a text response for tasks such as image description, visual question answering, scene understanding, and structured visual analysis.

Why Choose This?

  • Image understanding with natural-language prompts Ask questions about an image or request a description in plain English.

  • Flexible response control Adjust max_tokens, temperature, and top_p to balance response length, determinism, and creativity.

  • Optional system steering Use system_prompt to guide output style, role, or response constraints for more controlled behavior.

  • Reasoning mode options Choose between no_think and think depending on your preferred response mode.

  • Production-ready API Suitable for image analysis workflows, multimodal assistants, automated review pipelines, and visual understanding tools.

Parameters

ParameterRequiredDescription
promptYesEnglish text prompt sent to the model.
imageYesImage URL to analyze with the model.
system_promptNoOptional system prompt used to steer behavior, tone, or response style.
reasoning_modeNoReasoning mode: no_think (default) or think.
max_tokensNoMaximum number of tokens to generate. Default: 1024.
temperatureNoSampling temperature. Lower values are more deterministic. Default: 0.7.
top_pNoNucleus sampling probability mass. Default: 0.95.

How to Use

  1. Upload or link your image — provide the image you want the model to analyze.
  2. Write your prompt — ask the model to describe, explain, compare, classify, or answer questions about the image.
  3. Add a system prompt (optional) — guide the response style, output format, or task framing.
  4. Choose reasoning mode (optional) — use no_think or think depending on your workflow.
  5. Set generation controls (optional) — adjust max_tokens, temperature, and top_p.
  6. Submit — run the model and review the generated response.

Example Prompt

Describe this image in detail, including the setting, visible objects, mood, and any notable historical or architectural details.

Pricing

Billed by configured max_tokens.

Max TokensCost
1000$0.006
1024$0.0061
2000$0.012
4000$0.024
8000$0.048

Billing Rules

  • Pricing is based on the configured max_tokens value.
  • Cost is $0.006 per 1,000 max tokens.
  • Increasing max_tokens increases cost linearly.
  • prompt, image, system_prompt, reasoning_mode, temperature, and top_p do not change pricing directly.

Best Use Cases

  • Image description — Generate clear descriptions of scenes, objects, and visual content.
  • Visual question answering — Ask targeted questions about what appears in an image.
  • Document and screenshot analysis — Extract meaning from UI screenshots, charts, diagrams, or other visual references.
  • Content moderation and review workflows — Use text prompts to guide structured inspection of uploaded images.
  • Multimodal assistants — Add image-aware understanding to support bots, tools, and internal workflows.
  • Research and annotation tasks — Use guided prompts to summarize or analyze visual inputs consistently.

Pro Tips

  • Write prompts in English for best compatibility.
  • Be specific about what you want, such as description, object listing, comparison, or focused analysis.
  • Use system_prompt when you need a consistent format, such as bullet summaries, JSON-style output, or domain-specific tone.
  • Keep temperature lower when you want more stable and deterministic responses.
  • Increase max_tokens only when you need longer outputs, since pricing is tied to that value.
  • Use top_p and temperature together carefully to balance diversity and control.

Notes

  • Both prompt and image are required.
  • prompt is English only.
  • Default settings include reasoning_mode = no_think, max_tokens = 1024, temperature = 0.7, and top_p = 0.95.
  • Pricing depends on configured max_tokens, not on other generation settings.

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