Developers Plead for Stable GPT-4o API Amid Forced Migration to GPT-5.1

In a recent social media post, a developer operating under the handle "ForO_Koshi" issued a direct appeal to OpenAI leadership, including CEO Sam Altman, for a "stable snapshot locked until 2025" of the GPT-4o model. The plea comes as OpenAI has announced the deprecation of GPT-4o API access by February 16, 2026, compelling developers to migrate to newer models like the GPT-5.1 series. This move has ignited significant frustration within the developer community, who cite concerns over "silent breakage" and the need for a "minimum trust anchor."

OpenAI's decision to sunset GPT-4o API access is part of a broader strategy to accelerate the adoption of its latest and more efficient models, such as GPT-5.1. The company highlights that GPT-5.1 offers substantial upgrades, including larger context windows, more advanced reasoning capabilities, higher throughput, and potentially lower input costs for developers. However, this rapid innovation cycle places a considerable burden on developers who have built production systems on GPT-4o.

The forced migration necessitates extensive work, including regression testing, prompt re-engineering, performance validation, and cost modeling, which can take weeks or months for development teams. Many developers have expressed that while newer models may offer improvements, the effort and potential instability of transitioning are significant. "OpenAI wants everyone on GPT-5.1," noted one industry analysis, "but forced migrations are never that simple."

Community forums reveal widespread concerns about the consistency of OpenAI's models over time, with some users reporting varying behavior even when using the same model version. The tweet's call for a "frozen 4o-2025-xx-xx build" directly addresses these issues, seeking a predictable and reliable version for ongoing development. This sentiment underscores a growing demand among developers for greater stability and longer support cycles for AI models, allowing them to build robust applications without constant re-engineering.