OpenAI released a guide for the GPT-6 family, offering practical advice on model selection, prompt optimization, and cost management. The guide is aimed at developers and teams looking to integrate GPT-6 models into their workflows.
What happened
OpenAI has published a comprehensive guide for the GPT-6 family of models, designed to help developers and teams effectively use these models in production environments. The guide covers several key areas including preparing workflows for production, matching models to specific workloads, and optimizing long-running tasks. It emphasizes the importance of choosing the right model based on the task requirements, such as GPT-6 Astra for complex reasoning tasks and GPT-6 Luna for focused, repetitive work. Additionally, the guide provides tips on adjusting prompts and managing costs through techniques like caching and compaction.
FAQ
What models are in the GPT-6 family?
The GPT-6 family includes GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna.
How do I choose the right model for my task?
Balance capability, cost, and latency by choosing the model, reasoning effort, and speed that fit the task.
What are the reasoning levels?
Low: Routine tasks, such as extracting facts or making small edits. Medium: Work requiring judgment, such as planning a feature or comparing options. High: Difficult debugging, deeper analysis, or careful review. Extra high / Max: Test where supported when High falls short, and keep only if the improvement justifies the added time and cost.
Source: OpenAI
