GPT-5 mini
GPT-5 mini is a text generation model from OpenAI with a 400,000-token context window and tool-use support.
OpenAIEfficient text generation with extended context
GPT-5 mini is a text generation model developed by OpenAI, released in August 2025. It supports a 400,000-token context window and can produce responses up to 128,000 tokens in length, making it suited for tasks that involve long documents or extended conversations. The model accepts image inputs alongside text and supports adjustable reasoning effort, giving developers control over how much computation the model applies to a given request.
GPT-5 mini is designed for use cases that require broad context handling, tool integration, and MCP (Model Context Protocol) server connectivity. Its tool-use support allows it to call external functions and APIs during inference, enabling agentic workflows. The model is a good fit for developers building applications that need to process large volumes of text, coordinate multi-step tasks, or connect to external data sources through standardized protocols.
What GPT-5 mini supports
Long Context Window
Processes up to 400,000 tokens of input in a single request, enabling analysis of large documents, codebases, or extended conversation histories.
Extended Response Length
Generates responses of up to 128,000 tokens, supporting long-form outputs such as detailed reports, lengthy code files, or multi-section documents.
Image Understanding
Accepts image inputs alongside text prompts, allowing the model to analyze, describe, or reason about visual content within a conversation.
Tool Use
Supports function calling and external tool integration, enabling the model to invoke APIs or structured functions during inference for agentic workflows.
MCP Server Support
Connects to Model Context Protocol servers, allowing standardized access to external data sources and services without custom integration code.
Adjustable Reasoning Effort
Exposes a reasoning effort setting that lets developers tune how much computation the model applies per request, balancing speed against response depth.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 83.7% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 82.8% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 83.8% |
| HLE | Questions that challenge frontier models across many domains | 19.7% |
| SciCode | Scientific research coding and numerical methods | 39.2% |
Common questions about GPT-5 mini
What is the context window size for GPT-5 mini?
GPT-5 mini supports a context window of 400,000 tokens, meaning it can process up to that many tokens of combined input and conversation history in a single request.
How long can GPT-5 mini's responses be?
The model can generate responses of up to 128,000 tokens in a single output, which is suitable for long-form content such as detailed reports or extensive code.
Does GPT-5 mini support image inputs?
Yes, GPT-5 mini accepts image inputs alongside text, allowing it to process and reason about visual content within a prompt.
What is the reasoning effort setting?
Reasoning effort is a configurable input that controls how much computation the model applies when generating a response. Adjusting it lets developers trade off between response speed and depth of reasoning.
What is the release date of GPT-5 mini?
GPT-5 mini was released in August 2025 by OpenAI.
Does GPT-5 mini support tool use and MCP servers?
Yes, the model supports both function calling via tools and connectivity to Model Context Protocol (MCP) servers, making it suitable for agentic and multi-step task workflows.
What people think about GPT-5 mini
Community discussion around GPT-5 mini's launch was driven largely by a viral Reddit post about an alleged internal leak of GPT-5's model description on GitHub, which generated over 1,000 upvotes and 142 comments on r/ChatGPT. Users expressed significant interest in the model's capabilities and the circumstances of the leak.
Commenters raised questions about the accuracy of the leaked information and what it revealed about GPT-5's design, with some skepticism about the leak's authenticity. The thread reflects broad community curiosity about the GPT-5 family rather than direct hands-on feedback about GPT-5 mini specifically.
Parameters & options
Used to give the model guidance on how many reasoning tokens it should generate before creating a response to the prompt. Low will favor speed and economical token usage, and high will favor more complete reasoning at the cost of more tokens generated and slower responses. The default value is medium, which is a balance between speed and reasoning accuracy.
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