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GPT
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OpenAI's universal model for text, analysis and logic, with a thinking mode (Thinking Mode) and personalisation.
What it is
Text, analysis, logic.
GPT-5 came out in August 2025, and the GPT-5.1 update followed in November. In it, OpenAI focused strongly on "thinking" and personalisation. GPT-5 uses a built-in chain of reasoning (similar to the o1/o3 series) to plan its answers to complex questions. The "Quick Reset" and "Deep Recalibration" features let you manage the load on the model. GPT-5.1 added deep personalisation settings: you can tune "warmth", "enthusiasm" and formatting style.
What it does
What it does
- Thinking Mode: built-in chain of reasoning for complex questions
- Deep personalisation: tuning warmth, enthusiasm and style
- Project-only memory keeps preferences across conversations
- 400K token context window (a large volume of text at once) for working with extensive documents
- Quick Reset and Deep Recalibration for managing the load on the model
Good for
- Creating content and structuring information
- Analysing complex problems and product logic
- Working with extensive documents thanks to the 400K token context
Not for
- Demanding programming and code changes (Claude is a better fit)
- Free creative exploration of ideas and brainstorming (Gemini is a better fit)
Our verdict
Our main language model for text, analysis and logic. Thinking Mode and personalisation make it a reliable foundation, which we complement with Claude for code and Gemini for exploring ideas.
Why we use it
We use GPT-5 for text, analysis and logic. The model excels at general reasoning, personalisation and handling complex questions. It suits creating content, structuring information, analysis and supporting product logic. Thinking Mode allows deeper reasoning about complex problems, and personalisation keeps the same style across conversations.
Use cases
Use cases
Content creation
Generating text using Thinking Mode for more complex tasks and personalisation for a consistent style.
Analysis and logic
Analysing complex problems and structuring information, using the 400K token context for working with extensive documents.
Product logic
Supporting product logic and decisions, using project-only memory, which keeps context across conversations.
Structuring information
Organising and structuring information, using Thinking Mode for deeper understanding and personalisation for the preferred format.
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