---
title: GPT-5-nano — Fast, Cost-Efficient LLM | ModelsLab
description: Generate text with GPT-5-nano. Fastest, cheapest GPT-5 model for summarization, classification, and real-time applications. Start now.
url: https://modelslab.com/gpt-5-nano
canonical: https://modelslab.com/gpt-5-nano
type: website
component: Seo/ModelPage
generated_at: 2026-04-24T23:28:25.652882Z
---

Available now on ModelsLab · Language Model

GPT-5-nano
Speed meets efficiency
---

[Try GPT-5-nano](/models/openai/gpt-5-nano) [API Documentation](https://docs.modelslab.com)

![GPT-5-nano](https://assets.modelslab.ai/generations/264a17fd-e3e6-4145-a644-88e3c644638f.webp)

Extreme Performance. Extreme Value.
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Lightning-Fast

### 50-60 Tokens Per Second

Process more reasoning per dollar with industry-leading token throughput and 180ms first-token latency.

Ultra-Affordable

### 20-25× Cheaper Than Alternatives

Pay $0.05 per million input tokens. Ideal for high-volume, cost-sensitive production workloads.

Built for Scale

### 400K Context Window

Handle long documents, codebases, and transcripts without truncation or session limits.

Examples

See what GPT-5-nano can create
---

Copy any prompt below and try it yourself in the [playground](/models/openai/gpt-5-nano).

Document Summarization

“Summarize this quarterly earnings report into 3 key takeaways: \[paste full report\]. Focus on revenue, margins, and forward guidance.”

Email Classification

“Classify this customer email as: urgent, follow-up, or resolved. Email: \[paste text\]. Respond with classification only.”

Code Snippet Generation

“Write a Python function that validates email addresses using regex. Include error handling and return True/False.”

Meeting Notes Extraction

“Extract action items, decisions, and owners from this meeting transcript: \[paste transcript\]. Format as bullet points.”

For Developers

A few lines of code.
Fast inference. Minimal cost.
---

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 GPT-5-nano
---

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

### What is GPT-5-nano best used for?

GPT-5-nano excels at summarization, classification, boilerplate generation, and real-time applications where speed and cost matter more than deep reasoning. It's optimized for production workloads like chatbots, routing layers, and agent backends.

### How does GPT-5-nano compare to other GPT-5 models?

GPT-5-nano is the smallest, fastest, and cheapest variant in the GPT-5 lineup. It trades reasoning depth for speed and cost efficiency, making it ideal for high-throughput tasks. Larger GPT-5 models handle complex reasoning and multi-step problem-solving.

### What are the pricing and token limits for GPT-5-nano API?

GPT-5-nano costs $0.05 per million input tokens and $0.40 per million output tokens, with cached-input pricing at $0.005 per million tokens. It supports a 400K token input context window and 128K token output limit.

### Can GPT-5-nano handle images?

Yes, GPT-5-nano accepts both text and image inputs. However, it outputs text only—it cannot generate images, audio, or other media formats.

### How fast is GPT-5-nano compared to GPT-4o?

GPT-5-nano achieves ~180ms first-token latency and 50-60 tokens per second throughput. While GPT-4o excels at low-latency voice (~232ms), GPT-5-nano delivers superior token throughput and reasoning efficiency per dollar for text workloads.

### Is GPT-5-nano suitable for complex reasoning tasks?

GPT-5-nano is optimized for efficiency over complex reasoning. It handles simple procedural math and straightforward logic well but may struggle with multi-step proofs, abstract reasoning, or tool orchestration. For complex tasks, use larger GPT-5 variants.

Ready to create?
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Start generating with GPT-5-nano on ModelsLab.

[Try GPT-5-nano](/models/openai/gpt-5-nano) [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 - 2026-04-25*