AI developers\u00a0<\/a> can fine-tune how deeply the model thinks by using the new reasoning_effort parameter. It includes a \u201cminimal\u201d option for faster, less detailed answers when speed matters more than depth. There\u2019s also a verbosity setting to choose whether responses should be short, medium, or long. This means you do not need to rewrite your prompts.<\/p>\n2. Simplified Custom Tool Calls<\/strong><\/p>\nGPT-5 supports \u201ccustom tools\u201d that can be invoked using plain text instead of JSON. This avoids tricky escape characters that used to cause problems, especially with complex outputs like big code blocks. Plus, you can enforce your own output formats by restricting tool calls with regex or full grammars.<\/p>\n
3. Better at Complex, Multi-Step Tasks<\/strong><\/p>\nThe model is much stronger at handling extended, multi-step workflows. It can manage dozens of tool calls\u2014both in sequence and parallel\u2014without losing track of context or mixing things up.<\/p>\n
4. Improved Front-End Coding<\/strong><\/p>\nIn internal tests, GPT-5 outperformed the previous OpenAI o3 model about 70% of the time when generating front-end code, producing cleaner, more visually appealing interfaces with superior layouts, typography, and spacing.<\/p>\n
5. Massive Context Capacity & Reduced Hallucinations<\/strong><\/p>\nOn the API side, GPT-5 now supports a combined input\/output context length of up to 400,000 tokens. Benchmarks show it retrieves relevant information from large inputs far more accurately than before, while significantly reducing hallucination rates on factual tasks.<\/p>\n
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