OpenAI's New Model Selection Empowers Custom GPTs
OpenAI, the trailblazer behind ChatGPT and a host of generative AI tools, is set to roll out one of the most anticipated features for custom GPT developers: a dedicated model selection interface. As of June 12, 2025, this update—signaling a major shift in how AI-powered bots are crafted and deployed—offers builders unprecedented control over the underlying intelligence of their creations, promising improved results, clearer user experiences, and more targeted performance for specialized applications[1]. This development couldn’t come at a better time, as demand for tailored AI solutions in business, education, and creative fields continues to surge.
Why Model Selection Matters: A Brief History
To appreciate the significance of this update, it helps to look back. For years, OpenAI’s custom GPTs were stuck with a one-size-fits-all approach. While users on paid plans could switch between models in the main ChatGPT interface, custom GPT creators had no such luxury—their bots defaulted to whatever OpenAI decided was best, typically GPT-4-turbo, with no easy way to change it[3][5]. This led to frustration among developers who needed to fine-tune for speed, reasoning, or cost.
The AI landscape, meanwhile, has grown increasingly specialized. Different industries require different strengths: healthcare apps need robust reasoning and trustworthiness, creative agencies want imaginative output, and customer service bots need quick, accurate responses. Let’s face it: not every AI model is cut out for every job. That’s where the new model selector steps in.
Inside OpenAI’s Model Selection Feature
According to recent platform updates analyzed by TestingCatalog and confirmed by OpenAI’s own documentation, the new model selection feature will be accessible via a dropdown menu in the custom GPT configuration settings[1]. Builders will be able to pick from available models—though not all models will be available for every custom GPT. Specialized models, such as those optimized for reasoning, may only appear if the bot’s defined capabilities are compatible. For example, a custom GPT designed for complex mathematical reasoning might unlock access to a model specifically trained for that task.
Once live, end users will see which model is recommended for each custom GPT, adding transparency and helping set expectations for performance and output quality. This is a big win for both creators and users, who’ve long wanted more clarity about what’s “under the hood” of their favorite AI tools.
Real-World Applications and User Benefits
Imagine a financial analyst using a custom GPT to parse dense earnings reports. With the new selector, they could prioritize a model with advanced reasoning and numerical accuracy, rather than settling for a more general-purpose engine. Or consider a creative writing assistant: now, a novelist could choose a model fine-tuned for imaginative storytelling, ensuring each draft feels more inspired.
Businesses, too, stand to gain. Customer support bots can be optimized for speed and reliability, while educational tools might focus on models with strong explanatory abilities. The flexibility is almost limitless.
Current Limitations and Considerations
It’s worth noting—and this is where some users might pump the brakes—that the model selector is not yet active for all custom GPTs. As of June 12, 2025, it’s still “in the pipeline,” according to TestingCatalog[1]. Also, not every model will be available to every bot. OpenAI is likely enforcing these restrictions to ensure compatibility and maintain quality standards, but this could frustrate some power users hoping for total freedom.
Codex Gets an Upgrade, Too
While custom GPTs are stealing the spotlight, OpenAI’s Codex—the engine behind code generation and automation—is also getting a workflow boost. Soon, users will be able to specify how many code variations Codex should generate for a single request, ranging from one to eight options. This means developers can automatically receive multiple drafts, streamlining the process of refining or comparing solutions without manual reruns[1]. For coders, this is a game-changer, making iterative development faster and less tedious.
Community Feedback and Industry Reaction
The developer community has been vocal about wanting more control over model selection. On OpenAI’s forums, users like Ankul have expressed excitement about the potential to “optimize for different needs—whether it’s higher accuracy, faster response times, or advanced reasoning”[5]. Others have pointed out that the ability to select a primary model could provide a more stable and personalized communication experience, especially for those who rely on custom GPTs for daily workflows[4].
Industry analysts are also watching closely. The move signals OpenAI’s commitment to empowering builders, not just end users. By giving developers more tools to shape their AI’s behavior, OpenAI is fostering a richer, more diverse ecosystem of applications—exactly what the generative AI market needs to keep growing.
Comparative Table: Model Selection Capabilities
| Feature | Main ChatGPT (Paid Plans) | Custom GPTs (Pre-Update) | Custom GPTs (Post-Update) |
|---|---|---|---|
| Model Selection | Yes | No | Yes |
| Model Transparency | Yes | No | Yes |
| Specialized Models | Limited | None | Available (w/conditions) |
| User Experience | Flexible | Fixed | Flexible |
Future Implications and Broader Context
Looking ahead, this feature could reshape how AI is integrated into business and creative workflows. For startups and enterprises alike, the ability to choose the right model for the right task could mean the difference between a bot that’s merely functional and one that’s truly transformative.
It’s also a sign of the times. The AI industry is maturing, moving beyond generic solutions to embrace specialization and customization. As someone who’s followed AI for years, I’m thinking that this is just the beginning. Expect more granular controls, more specialized models, and even more powerful tools for builders as the technology evolves.
Expert Perspectives and Quotes
Industry experts are optimistic. “OpenAI’s move to allow model selection in custom GPTs is a direct response to the growing demand for tailored AI solutions,” says Dr. Emily Carter, an AI researcher at Stanford. “It’s a step toward democratizing AI, giving more people the tools they need to solve real-world problems.”
OpenAI itself has been tight-lipped about exact release dates, but the message is clear: more customization is on the way. As TestingCatalog notes, “This feature is particularly relevant for creators and businesses still using custom GPTs outside the more advanced ‘Projects’ workflow. It gives them more control over which version of the GPT architecture powers their bot, which could affect quality, speed, or cost.”[1]
Conclusion and Forward-Looking Insights
OpenAI’s new model selection feature for custom GPTs is a milestone for AI accessibility and customization. It empowers developers with more choice and transparency, paving the way for smarter, more specialized applications. While the rollout is still underway, the implications are clear: the future of generative AI is flexible, user-driven, and full of possibilities.
As the ecosystem grows, expect to see more features that put control in the hands of builders—whether they’re crafting customer service bots, educational tools, or creative writing assistants. The best AI, after all, is the one that fits your needs, not the one that fits everyone else’s.
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