OpenAI Releases GPT-6 Usage Guide: Workload-Based Model Selection and Prompt Tips

OpenAI published a blog post on October 2 sharing guidance for its GPT-6 model family, aiming to help users manage time and cost while getting the most out of the models. The company describes GPT-6 as its most advanced model series to date, offering multiple variants for different workloads.

For model selection, OpenAI recommends choosing based on the task rather than defaulting to the most powerful model. Lighter models are often faster and cheaper for simple tasks. GPT-6 Astra is suited for the most difficult reasoning work, GPT-6.1 Sol for complex coding, research, and computer use, while GPT-6 Luna handles high-volume specific tasks and routine repetitive work such as extracting invoice fields, classifying requests, or generating structured summaries.

On prompt optimization, OpenAI suggests stating the desired outcome, audience, relevant context, constraints, and what counts as completion, rather than writing long step-by-step instructions. It also advises clarifying what the model can decide on its own and when it should ask for input.

Regarding reasoning effort, OpenAI notes that everyday questions do not require the highest setting; only complex analysis, debugging, or deep research warrants higher reasoning intensity.