Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now
The launch of OpenAI’s long anticipated new model, GPT-5, is off to a rocky start to say the least.
Even forgiving errors in charts and voice demoes during yesterday’s livestreamed presentation of the new model (actually four separate models, and a ‘Thinking’ mode that can be engaged for three of them), a number of user reports have emerged since GPT-5’s release showing it erring badly when solving relatively simple problems that preceding OpenAI models — and rivals from competing AI labs — answer correctly.
For example, data scientist Colin Fraser posted screenshots showing GPT-5 getting a math proof wrong (whether 8.888 repeating is equal to 9 — it is of course, not).
It also failed on a simple algebra arithmetic problem that elementary schoolers could probably nail, 5.9 = x + 5.11.
AI Scaling Hits Its Limits
Power caps, rising token costs, and inference delays are reshaping enterprise AI. Join our exclusive salon to discover how top teams are:
Turning energy into a strategic advantage
Architecting efficient inference for real throughput gains
Unlocking competitive ROI with sustainable AI systems
Secure your spot to stay ahead: https://bit.ly/4mwGngO
Using GPT-5 to judge OpenAI’s own erroneous presentation charts also did not yield helpful or correct responses.
It also failed on this trickier math word problem below (which, to be fair, stumped this human at first…though Elon Musk’s Groq 4 AI answered it correctly. For a hint, think of the fact that flagstones in this case can’t be divided into smaller portions. They must remain in tact as 80 separate units, so no halves or quarters).
Not as good at coding as benchmarks indicate
Even though OpenAI’s internal benchmarks and some third-party external ones have shown GPT-5 to outperform all other models at coding, it appears that in real world usage, Anthropic’s recently updated Claude Opus 4.1 seems to do a better job at “one-shotting” certain tasks, that is, completing the user’s desired application or software build to their specifications. See an example below from developer Justin Sun posted to X :
Unfortunately, OpenAI is slowly deprecating those older models — including the former default GPT-4o and the powerful reasoning model o3 — for users of ChatGPT, though they’ll continue to be available in the application programming interface (API) for developers for the foreseeable future.
In addition, a report from security firm SPLX found that OpenAI’s internal safety layer left major gaps in areas like business alignment and vulnerability to prompt injection and obfuscated logic attacks.
While anecdotal, the checking the temperature on how the model is faring with early AI adopters seems to indicate a chilly reception.
AI influencer and former Googler Bilawal Sidhu posted a poll on X asking for a “vibe check” from his followers and the wider userbase, and so far, with 172 votes in, the overwhelming response is “Kinda mid.”
And as the pseudonymous AI Leaks and News account wrote, “The overwhelming consensus on GPT-5 from both X and the Reddit AMA are overwhelmingly negative.”
Tibor Blaho, lead engineer at AIPRM and a popular AI leaks and news poster on X, summarized the many problems with the ChatGPT-5 rollout in an excellent post, highlighting that one of the new marquee features — an automatic “router” in ChatGPT that chooses a thinking or non-thinking mode for the underlying GPT-5 model depending on the difficulty of the query — has become one of the chief complaints, given the model seemed to default to non-thinking mode for many users.
Competition waiting in the wings
Thus, the sentiment toward ChatGPT-5 is far from universally positive, highlighting a major problem for OpenAI as it faces increasing competition from major U.S. rivals like Google and Anthropic, and a growing list of free, open source and powerful Chinese LLMs offering features that many U.S. models lack.
Take the Alibaba Qwen Team of AI researchers, who just today updated their highly performant Qwen 3 model to have 1 million token context — giving users the ability to exchange nearly 4x as much information with the model in a single back/forth interaction as GPT-5 offers.
Given OpenAI’s other big release this week — that of new open source gpt-oss models — also received a mixed reception from early users, things are not looking up for the number one dedicated AI company by users right now (700 million weekly active users of ChatGPT as of this month).
Indeed, this is also exemplified by users of the betting marketplace Polymarket overwhelmingly deciding following the release of GPT-5 that Google would likely have the best AI model by the end of this month, August 2025.
Other power users like Otherside AI co-founder and CEO Matt Schumer, who received early access to GPT-5 and blogged about it favorably in a review here, opined that views would shift as more people figured out the best ways to use the new model and adjusted their integration approaches:
While it’s still early days for GPT-5 — and the sentiment could change dramatically as more users get their hands on it and try it for different tasks — the early indications are not looking like this is a “home run” release for OpenAI in the same way that prior releases such as GPT-4, or even the newer 4o and o3, were. And that’s a concerning indicator for a company that just raised yet another funding round, yet remains unprofitable due to its high costs of research and development.
