Last week marked the much-anticipated launch of GPT-5, escalating excitement within the AI community to unprecedented levels.
Prior to the event, OpenAI CEO Sam Altman emphasized the significance of GPT-5, likening it to the introduction of the first iPhone with a Retina display. Just before the announcement, he shared an image of the Death Star on social media, which intensified the anticipation. Enthusiastic reactions flooded platforms like X, with one user likening the excitement to “Christmas Eve.” Industry observers eagerly awaited the unveiling, but it appears the reality may not have met the lofty expectations set by the build-up.
Anticipation for OpenAI’s new model has been mounting ever since the release of GPT-4 in 2023. During a Reddit AMA session with Altman and OpenAI staff last October, users pressed for details about GPT-5’s release date and distinguishing features. Altman mentioned computational limitations, explaining that the complexity of the models restricts parallel development.
When GPT-5 finally became available, many users found the advancements somewhat muted. The significant improvements they were expecting primarily involved cost and processing speed rather than groundbreaking features. While these enhancements might be beneficial from a financial perspective, they lacked the striking innovation anticipated by the public.
Expectations were exceptionally high following Altman’s pre-launch teasers, which left many feeling let down. OpenAI characterized GPT-5 as its “best AI system yet,” and Altman described user interactions as akin to conversing with a PhD-level expert. Such bold claims set the stage for a significant letdown when users encountered the model’s limitations.
The contrast between the hype and the actual performance was stark. Users reported flaws such as incorrectly identifying the number of “b’s” in the word “blueberry” and mislabeling geographical locations. Some even expressed dissatisfaction with the emotional support provided by the bot, prompting OpenAI to reintroduce a prior model that users found more comforting. Comical memes circulated online, depicting GPT-4 and its predecessor as powerful creatures, while GPT-5 was portrayed in a less flattering light.
Expert opinions have echoed user sentiments. Gary Marcus, an influential voice in the AI sector, labeled GPT-5 as “overdue, overhyped and underwhelming.” Similarly, Peter Wildeford remarked that it failed to meet the high expectations, while Zvi Mowshowitz described it as “a good, but not great, model.” Responses from Reddit users were also critical, with one remarking that GPT-5 was “hot garbage.”
As the initial wave of reviews subsided, the sentiment seemed to stabilize. Although not as groundbreaking as anticipated, GPT-5 did deliver improvements in terms of cost, speed, and a new back-end query switching system that enhances user experience. Altman highlighted that the focus with GPT-5 was on real-world utility and accessibility.
OpenAI researcher Christina Kim echoed this sentiment, stating that GPT-5 aims to enhance usability by assisting with coding, creative writing, and health information more efficiently. She emphasized its better handling of inaccuracies and misleading information, underlining its improved grounding capabilities.
However, many users noted a decline in linguistic finesse, describing GPT-5’s output as more robotic and less nuanced than previous iterations. Even OpenAI’s promotional comparisons between GPT-4o and GPT-5 in generating wedding toasts showcased a lack of engagement in the newer model’s performance, leading to backlash on social media against Altman’s claim of superior writing capabilities.
Conversely, GPT-5 has garnered praise for its coding capabilities, currently ranking atop the AI coding model leaderboard, surpassing competitors like Anthropic’s Claude. OpenAI promoted its various coding applications during the launch, including a mini-game and a pixel art tool. While certain functionalities experienced glitches, simpler tasks, like coding an interactive lesson, displayed promising results.
This success is crucial for OpenAI as it competes in the lucrative AI coding landscape, where businesses invest heavily. Coding remains a vital revenue stream for AI startups amid the pursuit of profitability.
OpenAI also touted GPT-5’s capabilities in healthcare, although practical applications remain to be fully evaluated over time.
Despite AI benchmarks evolving rapidly and their reliability sometimes being questioned, GPT-5 performed reasonably well in industry evaluations. While it did show marginal improvements over previous versions, experts noted that these enhancements did not justify the pre-launch hype surrounding the model.
Looking ahead, the incremental improvements found in GPT-5 may more effectively translate into substantial profit rather than simply impressing consumers. AI companies are increasingly aware that their most significant revenue may come from enterprise customers, government contracts, and strategic investments. A focus on refining benchmarks and enhancing coding accuracy is essential for maximizing these opportunities.
