Model series and product entrance
OpenAI's GPT series provides capabilities through different products and APIs. The current official selection document uses Astra for difficult analysis and complex delivery, GPT-6.1 Sol for complex work that takes into account capabilities, time and cost, and Luna for clear scope and high-frequency tasks. This article introduces this division of labor and does not apply the rights and interests of a certain product package to all entrances.
Ability selection is not just "which one is stronger"
In the same entrepreneurial project, extracting table fields, comparing customer needs and designing system architecture require different depths of work. The official documentation also emphasizes that there are differences in model versions, inference settings, and tool availability. Even if the input is the same and more reasoning is invested, there is no guarantee that every answer will be improved. It still needs to be compared with actual samples.
How can small teams divide labor (ChinaOPC analysis)
When creating customer solutions, you can organize the classification of confirmed data into tasks with clear scope, and then hand over data conflicts, solution selection and delivery structures to models that are more suitable for complex problems. The premise of such allocation is that each step has clear output and review standards, and the model name alone cannot determine whether the work is completed.
For example, when extracting ten requirements from a customer record, checking field integrity is often more important than generating long descriptions. When it comes to evaluating demand priorities, it is necessary to analyze resources, time and customer goals. Separating these two steps can help identify sources of errors and determine whether upgrading the model is truly valuable.
How to do a small comparison
Choose a job that will happen repeatedly and compare candidate configurations using the same inputs, the same output formats, and the same acceptance rules. Record factual errors, omissions, wait times, and manual rework, not just answer length. Find a solution that meets the criteria first, and then consider whether it's worth investing in a more complex model.
What to check before accessing
It is necessary to confirm the region where the account is located, the available range of products and specific models, and whether tools such as networking, files, and code execution are open. Please refer to the current official instructions for web subscription, development tool quota and API billing respectively. When it comes to business documents, you should know what will be passed on to the service provider and use the minimum necessary information to complete the trial.
Continue to compare
Compare Claude's long-task collaboration; Understand MiniMax's task costs. You can also browse the AI model column.