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Text Generation Model

GPT-5

GPT-5 is a text generation model from OpenAI with a 400,000-token context window and adjustable reasoning effort.

PublisherOpenAI
TypeText
Context Window400,000 tokens
ReleasedAugust 2025
Input$1.25/MTok
Output$10.00/MTok
REASONINGTOOLSMCP

Reasoning and tool use at large context scale

GPT-5 is a large language model developed by OpenAI, released in August 2025. It supports text generation with a 400,000-token context window and a maximum response size of 128,000 tokens, making it suited for tasks that require processing or producing long-form content. The model accepts image inputs alongside text and exposes a configurable reasoning effort setting, allowing users to tune how much compute the model applies to a given problem.

GPT-5 is tagged for reasoning, tool use, and MCP (Model Context Protocol) support, meaning it can connect to external tools and servers during inference. This makes it applicable to agentic workflows where the model needs to call APIs, retrieve data, or coordinate across multiple steps. It is available as a first-party model on MindStudio without requiring a separate API key or OpenAI account.

What GPT-5 supports

Adjustable Reasoning

A configurable reasoning effort input lets users control how much computation the model applies per request, trading speed for depth of reasoning.

Tool Calling

Supports structured tool use so the model can invoke external functions or APIs during a conversation to retrieve data or take actions.

MCP Server Integration

Accepts MCP (Model Context Protocol) server configurations as a direct input, enabling connection to standardized external context and tool providers.

Image Understanding

Accepts image inputs alongside text prompts, supporting tasks like visual question answering, document analysis, and image description.

Long Context Processing

Handles up to 400,000 tokens of input context, suitable for processing lengthy documents, codebases, or multi-turn conversation histories.

Long-Form Output

Can generate responses up to 128,000 tokens, supporting detailed reports, extended code generation, and comprehensive document drafting.

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Benchmark scores

Scores represent accuracy — the percentage of questions answered correctly on each test.

BenchmarkWhat it testsScore
MMLU-ProExpert knowledge across 14 academic disciplines87.1%
GPQA DiamondPhD-level science questions (biology, physics, chemistry)85.4%
MATH-500Undergraduate and competition-level math problems99.4%
AIME 2024American math olympiad problems95.7%
LiveCodeBenchReal-world coding tasks from recent competitions84.6%
HLEQuestions that challenge frontier models across many domains26.5%
SciCodeScientific research coding and numerical methods42.9%
AIME 2025American math olympiad problems (2025)94.6%
SWE-bench VerifiedReal GitHub issues requiring multi-file code fixes74.9%

Common questions about GPT-5

What is the context window size for GPT-5?

GPT-5 has 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's responses be?

The maximum response size is 128,000 tokens, which supports generating lengthy documents, detailed code, or extended structured outputs in a single response.

Does GPT-5 support image inputs?

Yes, GPT-5 accepts image inputs alongside text, allowing it to analyze, describe, or answer questions about visual content.

What is the reasoning effort setting?

Reasoning effort is a configurable input that controls how much computation GPT-5 applies when generating a response. Increasing it can improve output quality on complex tasks at the cost of higher latency.

Does GPT-5 support tool use and MCP?

Yes. GPT-5 supports structured tool calling and accepts MCP (Model Context Protocol) server configurations, making it suitable for agentic workflows that require external API calls or data retrieval.

What is GPT-5's knowledge cutoff date?

OpenAI has not published a specific knowledge cutoff date in the available metadata for GPT-5. Check OpenAI's official documentation for the most current information on training data recency.

What people think about GPT-5

Community reception to GPT-5's launch was highly engaged, with thousands of upvotes and comments across multiple threads on r/ChatGPT, including a widely followed AMA with OpenAI's Sam Altman and the GPT-5 team. Users expressed significant interest in the model's coding and reasoning capabilities at release.

Some users raised concerns about whether the version deployed in ChatGPT matched the full API model, with one high-upvote thread questioning if a reduced variant was being served. A later thread noted the release of a GPT-5.2 update, suggesting ongoing iteration on the model after its initial launch.

View more discussions →

Parameters & options

Max Temperature1
Max Response Size128,000 tokens
Reasoning EffortSelect

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.

Default: medium
LowMediumHigh
ToolsTools
Web SearchAllow models to search the web for the latest information before generating a response.
Code InterpreterAllow models to write and run Python to solve problems.
mcpServersMCP Servers

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