GPT-5.4 API Model Guide
TL;DR
- Best for high-complexity reasoning, planning, and code analysis workflows.
- Uses OpenAI-compatible format: POST /v1/chat/completions for low-friction SDK migration.
- Supports stream=true SSE output for IDE copilots and real-time assistants.
Core Capabilities
- Complex reasoning and decomposition：Strong at long-chain reasoning, option comparison, and constraint-aware planning.
- High-quality code and technical writing：Useful for code explanation, refactoring proposals, tests, and technical drafts.
- OpenAI-compatible integration：Reuses Chat Completions payloads and existing SDK pipelines with minimal changes.
- Streaming for real-time UX：Supports stream=true for progressive rendering in interactive applications.
- Output controllability：Tune style and determinism with system prompts, temperature, top_p, and stop.
- Production-ready operation：Works well with auth, retries, rate controls, and observability practices.
When to Use
- When handling complex reasoning, technical evaluation, and coding analysis tasks.
- When you want OpenAI-compatible integration with minimal migration work.
- When streaming output is needed for responsive interactive UX.
When Not to Use
- For very low-complexity, high-volume tasks with strict cost constraints.
- For pure image/video generation workloads; use dedicated multimodal models instead.
Runtime Behavior
- Requests are sent to POST /v1/chat/completions using OpenAI Chat Completions format.
- stream=true returns SSE chunks, while stream=false returns a full response.
- Use choices and finish_reason for completion handling, with usage for token accounting.
Minimal Request
{
"model": "gpt-5.4",
"messages": [
{
"role": "system",
"content": "You are a senior backend engineer. Explain approach first, then code."
},
{
"role": "user",
"content": "Refactor this Node.js retry logic to exponential backoff and include a unit test."
}
],
"temperature": 0.3,
"max_tokens": 400,
"stream": false
}
Minimal Response
{
"id": "chatcmpl_xxxxxxxx",
"object": "chat.completion",
"created": 1703884800,
"model": "gpt-5.4",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "..."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 85,
"completion_tokens": 210,
"total_tokens": 295
}
}
Key Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|
| model | string | Yes | gpt-5.4 | - | Model ID for this page (for example gpt-5.4). |
| messages | object[] | Yes | - | - | Conversation messages in chronological order with system/user/assistant roles. |
| max_tokens | integer | No | - | >=1 | Maximum output tokens (model default applies when omitted). |
| stream | boolean | No | false | - | Whether to enable SSE streaming output. |
| temperature | number | No | 1 | 0-2 | Sampling temperature controlling randomness. |
| top_p | number | No | 1 | 0-1 | Nucleus sampling threshold; avoid aggressively tuning with temperature together. |
| stop | string | string[] | No | - | - |
| Authorization | HTTP Header | Yes | - | - | Bearer auth: Authorization: Bearer <YOUR_API_KEY>. |
Common Errors
| HTTP | Code | Trigger | Fix Action | Retry Policy |
|---|
| 400 | invalid_request_error | Missing required fields or invalid field types in payload. | Validate model, messages, and parameter types. | Retry only after fixing payload. |
| 401 | authentication_error | Missing/invalid auth header or invalid API key. | Verify Authorization header format and key validity. | Retry after auth is fixed. |
| 429 | rate_limit_error | Request rate, concurrency, or current quota hits upstream rate limiting. | Apply exponential backoff first, then review request rate, concurrency, and quota usage. | Use 1s/2s/4s backoff with jitter; if it persists, reduce submission pressure. |
FAQ
- What is GPT-5.4 best for?
It is best for complex reasoning, technical Q&A, code analysis, and high-quality content generation.
- What is the fastest integration path?
Use OpenAI-compatible format: POST to /v1/chat/completions with model and messages.
- How should streaming be handled?
Set stream=true and process SSE chunks incrementally, then finalize using finish_reason.
- How to choose temperature vs top_p?
Start with temperature first; tune top_p only when needed, and avoid over-tuning both together.
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