GPT-5 launches amid hype and mixed reviews

A look at GPT-5's launch amid hype and mixed reviews, noting gains in coding and affordability and criticisms of its pace and tone.

GPT-5 hype deflates as coding gains attract business

OpenAI released GPT-5 last week as hype built for years after GPT-4. Sam Altman called it a milestone and posted a Death Star image to tease the event. On launch day many expected a major leap. In practice, critics and users found the improvements smaller than hoped. The biggest wins were lower costs, faster responses, and fewer hallucinations. Some said the model was less eloquent in writing and more distant emotionally.

Code work showed promise. In tests the model performed well in coding tasks, and the developer tools to route queries to the best model were new. Healthcare work remained unproven. Benchmark results were mixed and some experts questioned the value beyond enterprise use. The business case may be in cost savings and enterprise contracts, not consumer awe. OpenAI said GPT-5 focuses on real world utility and accessibility, while investors watch how the model improves revenue streams.

OpenAI built GPT-5 in a long running hype cycle. The public excitement for a 'game changing' model clashed with early reviews that saw only incremental gains. The shift toward a model that prioritizes cost efficiency and reliability may align better with big buyers than with viral memes. This tension matters for OpenAI's business plan and for the wider AI market.

Expectations going forward will depend on real deployments. If enterprises win more credibility with stable tools, investors will pay. If not, the cycle of hype could hurt long term trust. The piece argues the future may hinge on practical utility and predictable performance more than spectacle.

Highlights

The tech cycle moves fast but trust comes from steady, verifiable gains