When OpenAI officially retired its legacy large language model GPT-4o (short for GPT-4 omni) from ChatGPT on February 13, 2026, the decision sparked immediate backlash across the digital landscape. Users mobilized on platforms such as X (formerly Twitter) and Reddit under hashtag campaigns like #keep4o and #OpenSource4o, vehemently protesting the phase-out and urging the company to reinstate access to the model or release its weights to the public.
According to an official OpenAI blog post addressing the shutdown, the tech giant justified the removal by citing shifting consumer behavior, claiming that “only 0.1% of users still choose GPT‑4o each day” as engagement moved toward newer systems like GPT-5.2. However, critics quickly disputed this metric as misleading. Power users and developers pointed out that calculating usage across ChatGPT’s global user base, which includes millions of free-tier accounts without access to legacy model options, diluted the true percentage of paying subscribers who relied on GPT-4o for daily workflows, creative writing, and human-like conversational warmth.
Fast forward to October 2026, and consumer frustration remains unresolved. Social media threads and dedicated forums continue to see daily posts demanding the return of GPT-4o, reflecting a persistent demand for legacy model preservation. Compounding this dissatisfaction are alleged reports from tech-savvy users who analyzed browser web traffic logs and API payloads. These users claimed to find evidence of silent, server-side rerouting, suggesting that even before the official February retirement, user queries directed at GPT-4o were occasionally intercepted and processed by underlying routing layers or alternate models without explicit user consent. Consequently, the community argues that OpenAI’s “0.1% daily usage” statistic was artificially deflated by system-level routing decisions, leaving a lasting rift between the platform and its most dedicated user base.
For example, take a look at the early large language model, the one from when ChatGPT first launched: “GPT-3.5 Turbo”. When I used it, it kept hallucinating too much and also had gaps in its training dataset, and it kept giving aggressive disclaimers like “As an AI language model” and “As of my last knowledge update of September 2021”. When it keeps happening, all that a user can do is send a large number of negative messages to the OpenAI support team. And also, GPT-3.5 Turbo was never open-sourced, so I couldn’t “fine-tune” it to reduce those hallucination errors, and OpenAI cited safety as one of the reasons, which, of course, I wasn’t planning on using the large language model to produce malware or anything like that. I was trying to reduce the hallucinations in the large language model itself. You can fine-tune in the developer platform itself, but you have to pay OpenAI for the fine-tuning and for how much you use it, and also you can only use it in the developer platform, and it wouldn’t change the user’s model or add it to ChatGPT. If you want to learn more about that GPT-3.5 Turbo retrospective, please read this article about it.
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