GPT-5 API Documentation: Endpoints, Models, and Best Practices
Build with Confidence on GPT-5
This practical guide distills the essential parts of the GPT-5 API so you can ship production-ready integrations fast. We cover authentication, model selection, request structure, token usage, streaming, and error handling—plus links to an integration guide and pricing insights.
Core Concepts
Authentication
Use a secret API key with Bearer auth. Never expose it in the browser. Rotate routinely and scope usage with server-side middleware.
Models
Start with gpt-5 for general tasks and gpt-5-reasoning for complex multi-step problems. Vision/audio/video are native with the same API.
Requests and Streaming
import OpenAI from "openai";
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const completion = await openai.chat.completions.create({
model: "gpt-5",
messages: [
{
role: "user",
content: [
{ type: "text", text: "Summarize this document" },
{ type: "image_url", image_url: { url: imageUrl } },
],
},
],
temperature: 0.2,
stream: true,
});GPT-5 supports server-sent events for low-latency token streaming. For browser UIs, proxy via your backend to keep keys secret and apply rate limits.
Errors, Limits, and Reliability
- • Implement retries with exponential backoff for 429/5xx responses.
- • Use idempotency keys for critical writes.
- • Log prompt/response metadata and token usage per request.
- • Respect per-minute and per-day rate limits; batch where possible.
- • Validate multimodal inputs (image/audio/video) before sending.
Next Steps
Ready to implement? Follow our step-by-step GPT-5 Integration Guide, compare GPT-5 vs GPT-4 differences, and review ChatGPT-5 API pricing.