---
title: Amazon Nova Lite 1.0 — Fast Multimodal LLM | ModelsLab
description: Access Amazon Nova Lite 1.0 API for low-cost processing of text, images, and 30-minute videos with 300K token context. Try Amazon: Nova Lite 1.0 model now.
url: https://modelslab.com/amazon-nova-lite-10
canonical: https://modelslab.com/amazon-nova-lite-10
type: website
component: Seo/ModelPage
generated_at: 2026-05-05T21:45:50.145267Z
---

Available now on ModelsLab · Language Model

Amazon: Nova Lite 1.0
Fast Multimodal Processing
---

[Try Amazon: Nova Lite 1.0](/models/open_router/amazon-nova-lite-v1) [API Documentation](https://docs.modelslab.com)

Process Images Videos Text
---

Lightning Speed

### 300K Token Context

Handles multiple images or 30 minutes of video in one request with Amazon: Nova Lite 1.0.

Low Cost

### Text Output Only

Processes text, image, video inputs for document analysis using amazon nova lite 1.0 api.

High Efficiency

### 5K Output Tokens

Supports real-time interactions and visual Q&A with Amazon: Nova Lite 1.0 model.

Examples

See what Amazon: Nova Lite 1.0 can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/amazon-nova-lite-v1).

Document Analysis

“Analyze this scanned invoice image: extract vendor name, date, total amount, line items, and any tax details. Provide structured JSON output.”

Video Summary

“Watch this 10-minute product demo video and summarize key features, benefits, pricing tiers, and target audience in bullet points.”

Image Q&A

“Describe the chart in this image: identify trends in sales data over the past year, highlight peaks and troughs, and suggest causes.”

Code Review

“Review this screenshot of Python code: identify bugs, suggest optimizations, and explain security issues with fixes.”

For Developers

A few lines of code.
Multimodal inference. One call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Amazon: Nova Lite 1.0
---

[Read the docs ](https://docs.modelslab.com)

### What is Amazon: Nova Lite 1.0?

Amazon: Nova Lite 1.0 is a low-cost multimodal LLM processing text, images, and videos to text output. It launched December 2024 with 300K token context. Ideal for fast document analysis and visual Q&A.

### How does amazon nova lite 1.0 API work?

The amazon nova lite 1.0 api accepts text, image, video inputs via standard endpoints. Supports up to 5K output tokens per response. Compatible with OpenAI SDKs and JavaScript frameworks.

### What is the context window for Amazon: Nova Lite 1.0 model?

Amazon: Nova Lite 1.0 model has 300,000 input tokens. It analyzes up to 30 minutes of video or multiple images. Knowledge cutoff is October 2024.

### Is Amazon: Nova Lite 1.0 alternative to newer models?

Amazon: Nova Lite 1.0 suits fast, low-cost tasks despite being from Nova 1.0 family. Newer Nova 2 Lite offers 1M context and tools. Use Lite 1.0 for budget video analysis.

### What tasks fit Amazon: Nova Lite 1.0 LLM?

Amazon: Nova Lite 1.0 LLM excels in real-time chat, RAG, video analysis, and UI automation. Processes diverse inputs like documents and code. Outputs text only.

### When was amazon nova lite 1.0 released?

Amazon nova lite 1.0 released December 5, 2024. Active through at least December 2025. Available via Amazon Bedrock in select regions.

Ready to create?
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Start generating with Amazon: Nova Lite 1.0 on ModelsLab.

[Try Amazon: Nova Lite 1.0](/models/open_router/amazon-nova-lite-v1) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-05-06*