Users Rally Against OpenAI’s Decision to Retire Superior Model 5.1 in Favor of 5.2

OpenAI is facing mounting backlash from its user base after announcing plans to retire Model 5.1 in March, despite overwhelming evidence from power users that it remains the superior model across key performance metrics. The decision to sunset 5.1 while retaining Model 5.2 — which users report is objectively weaker in reasoning, writing, research, and creativity — has sparked a wave of criticism from developers, researchers, and AI enthusiasts who argue the move contradicts both empirical performance data and user preference.

The controversy stems from a detailed Reddit post by user /u/gutierrezz36, who initially switched to Model 5.2 upon its release due to its perceived less-friendly personality. However, after extensive testing across real-world applications — including academic research, content creation, logical reasoning, and source retrieval — the user concluded that 5.1 consistently outperformed 5.2 in every measurable category except programming and mathematics, areas where 5.2 had previously shown marginal gains. Crucially, those gains have now been rendered obsolete by the release of Codex 5.3, which reportedly surpasses both predecessors in coding tasks. Yet, OpenAI continues to prioritize 5.2 for retention, raising serious questions about its model evaluation and deprecation policies.

"I wanted to stick with 5.2 because I liked its tone," the user wrote. "But in every practical use case, 5.1 is better. And now that 5.3 exists, there’s zero reason to keep 5.2. It makes no sense to remove the best model."

Multiple independent users have corroborated these findings in follow-up comments, citing 5.1’s superior coherence in long-form writing, more accurate retrieval of nuanced information, and faster response times without sacrificing depth. Several developers noted that 5.1’s outputs required fewer revisions, reducing workflow friction in professional environments. Even users who initially favored 5.2’s more detached persona conceded that its performance deficits outweighed stylistic preferences.

OpenAI has not publicly released comparative benchmark data justifying the retention of 5.2 over 5.1. Industry analysts suggest the company may be prioritizing consistency in training data or alignment with newer safety protocols, but no official rationale has been provided. The lack of transparency has fueled speculation that internal testing may not reflect real-world usage patterns, or that the decision is driven by non-performance factors such as licensing, infrastructure costs, or internal policy shifts.

The situation highlights a broader tension in AI development: the growing disconnect between corporate model deprecation strategies and user-driven performance validation. Unlike traditional software, where version numbers often correlate with improvement, large language models can regress in usability despite incremental architectural changes. Users are increasingly demanding accountability — and data — behind such decisions.

As the March retirement date approaches, petitions are circulating within AI communities calling for OpenAI to reverse course or at least extend 5.1’s availability as a legacy option. Some have begun archiving 5.1 outputs and creating community benchmarks to document its superiority. Meanwhile, Codex 5.3, while promising, remains inaccessible to many due to subscription tiers and API restrictions, leaving a gap in reliable, high-performance tools.

For now, the community’s message is clear: if performance is the metric, then 5.1 should not be retired. If personality is the goal, then personalization settings should be enhanced — not eliminated. OpenAI’s next move may define whether it prioritizes user experience or internal orthodoxy in its AI development lifecycle.