--- title: GPT-5.4 Nano — Fast LLM Inference | ModelsLab description: Run OpenAI: GPT-5.4 Nano API for classification, extraction, and high-throughput tasks. Generate efficient responses with low latency now. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/openai-gpt-54-nano canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/openai-gpt-54-nano type: website component: Seo/ModelPage generated_at: 2026-05-13T10:36:19.175712Z --- Available now on ModelsLab · Language Model OpenAI: GPT-5.4 Nano Nano Speed. Full Power --- [Try OpenAI: GPT-5.4 Nano](/models/open_router/openai-gpt-5.4-nano) [API Documentation](https://docs.modelslab.com) Deploy GPT-5.4 Nano Now --- Ultra Low Cost ### 0.20/M Input Tokens Process OpenAI: GPT-5.4 Nano API at $0.20 per million input tokens for high-volume classification. 400K Context ### Handles Long Inputs OpenAI: GPT-5.4 Nano model supports 400,000 token context with 128,000 output for extraction tasks. Sub-Second Latency ### Optimized for Scale Use OpenAI: GPT-5.4 Nano LLM as alternative for ranking and sub-agents at high throughput. Examples See what OpenAI: GPT-5.4 Nano can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/openai-gpt-5.4-nano). Code Review “Review this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” Data Extraction “Extract key entities from this invoice text: Invoice #1234, Date: 2025-01-15, Client: Acme Corp, Amount: $2500, Due: 2025-02-15.” Text Classification “Classify this email as spam, urgent, or normal: Subject: Urgent payment required! Click here to verify account.” Summary Generation “Summarize this article abstract on quantum computing advancements in under 100 words.” For Developers A few lines of code. 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 ```

import requests

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

``` FAQ Common questions about OpenAI: GPT-5.4 Nano --- [Read the docs ](https://docs.modelslab.com) ### What is OpenAI: GPT-5.4 Nano? GPT-5.4 Nano is OpenAI's smallest model for speed-critical tasks like classification and data extraction. It replaces GPT-5 nano with better benchmarks. Supports text and image inputs. ### How does openai gpt 5.4 nano API pricing work? Input costs $0.20 per million tokens, cached input $0.02, output $1.25. Regional endpoints add 10% uplift. Ideal for high-volume OpenAI: GPT-5.4 Nano API use. ### What is the context window for OpenAI: GPT-5.4 Nano model? It has a 400,000 token context window and 128,000 max output tokens. Knowledge cutoff is Aug 31, 2025. Fits long documents in openai gpt 5.4 nano. ### When to use OpenAI: GPT-5.4 Nano alternative? Choose for bulk tasks like ranking or sub-agents where cost beats peak performance. Beats prior mini in coding benchmarks. OpenAI: GPT-5.4 Nano LLM scales workflows. ### Does openai: gpt-5.4 nano support tools? Supports function calling, web search, and structured outputs. Designed for agentic pipelines. Access via OpenAI: GPT-5.4 Nano API endpoints. ### Is OpenAI: GPT-5.4 Nano faster than GPT-5 mini? Yes, nano prioritizes low-latency for throughput over complex reasoning. Use for simple tasks at scale. Part of GPT-5.4 efficient lineup. Ready to create? --- Start generating with OpenAI: GPT-5.4 Nano on ModelsLab. [Try OpenAI: GPT-5.4 Nano](/models/open_router/openai-gpt-5.4-nano) [API Documentation](https://docs.modelslab.com) --- *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) --- *Generated by ModelsLab - 2026-05-13*