Model Guide

Gpt 5 4 Mini

Model ID: gpt-5-4-mini

Vendor: OpenAIModalities: ChatPrice: Input $0.15/1M, Output $0.90/1MUpdated: 2026-05-02

Gpt 5 4 Mini is a high-end general model for complex reasoning and high-quality text/code generation. This page focuses on OpenAI Chat Completions integration, key parameters, and production-oriented implementation.

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Model Overview

Quick Answer

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.

Gpt 5 4 Mini Model Features

Core Section

Core capabilities and practical engineering value

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.

How to Use Gpt 5 4 Mini API

Create an API key and set Authorization: Bearer <YOUR_API_KEY>.
POST to /v1/chat/completions with at least model and messages.
Tune max_tokens, temperature, top_p, and stop for your scenario.
Enable stream=true and process SSE chunks for real-time rendering.
Finalize with finish_reason and usage metrics for observability.

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.

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.

Key Parameters

Parameter	Type	Required	Default	Range	Description
model	string	Yes	gpt-5-4-mini	-	Model ID for this page (for example gpt-5-4-mini).
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	-	-	Stop sequence(s), up to 4 entries.
Authorization	HTTP Header	Yes	-	-	Bearer auth: Authorization: Bearer <YOUR_API_KEY>.

Common Errors

400 invalid_request_error

Trigger: Missing required fields or invalid field types in payload.

Fix: Validate model, messages, and parameter types.

Retry: Retry only after fixing payload.

401 authentication_error

Trigger: Missing/invalid auth header or invalid API key.

Fix: Verify Authorization header format and key validity.

Retry: Retry after auth is fixed.

429 rate_limit_error

Trigger: Request rate, concurrency, or current quota hits upstream rate limiting.

Fix: Apply exponential backoff first, then review request rate, concurrency, and quota usage.

Retry: Use 1s/2s/4s backoff with jitter; if it persists, reduce submission pressure.

FAQ

What is Gpt 5 4 Mini 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.

Mode Notes

Chat Completions with Gpt 5 4 Mini

OpenAI-compatible endpoint for low-friction SDK reuse.

Mode Parameters

modelmessagesmax_tokenstemperaturetop_pstopstream

Best Scenarios

General Q&A assistants
Code explanation and refactor guidance
Technical writing

Streaming with Gpt 5 4 Mini

Enable stream for incremental SSE output in real-time interfaces.

Mode Parameters

streammessagesmax_tokens

Best Scenarios

IDE copilots
Progressive chat rendering
Terminal assistants

Tool Calling with Gpt 5 4 Mini

Extend with external tools/functions where tool-capable workflows are enabled.

Mode Parameters

toolstool_choicemessagesmax_tokens

Best Scenarios

RAG-style assistant
Automated test execution
Multi-step agent workflows

Gpt 5 4 Mini

Model Overview

Quick Answer

Gpt 5 4 Mini Model Features

Complex reasoning and decomposition

High-quality code and technical writing

OpenAI-compatible integration

Streaming for real-time UX

Output controllability

Production-ready operation

How to Use Gpt 5 4 Mini API

When to Use

Runtime Behavior

Key Parameters

Common Errors

400 invalid_request_error

401 authentication_error

429 rate_limit_error

FAQ

What is Gpt 5 4 Mini best for?

What is the fastest integration path?

How should streaming be handled?

How to choose temperature vs top_p?

Mode Notes

Chat Completions with Gpt 5 4 Mini

Streaming with Gpt 5 4 Mini

Tool Calling with Gpt 5 4 Mini

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