OpenAI GPT-5 Launch: Entering the Era of Diminishing Returns?
August 10, 2025
OpenAI’s GPT-5 disappoints users with incremental improvements despite hype, highlighting why multi-model AI platforms provide better cost control and reliability for businesses.
GPT-5: The Reality Check AI Businesses Have Been Waiting For
The AI world held its breath as OpenAI finally unveiled GPT-5 this week, marking the company’s most anticipated release in over two years. Yet, within hours of launch, a surprising narrative emerged: thousands of users flooded Reddit with complaints, with one of the most upvoted posts titled “GPT-5 is horrible” garnering 4,600 upvotes and 1,700 comments. What happened to the revolutionary leap we were promised?
The Hype Versus Reality Gap
OpenAI positioned GPT-5 as the moment when the company would “finally cement its dominance,” with CEO Sam Altman claiming “We think you will love using GPT-5 much more than any previous AI. It is useful it is smart it is fast [and] intuitive”. However, the reception tells a different story.
GPT-5 has underwhelmed many with its benchmark scores, managing just 56.7% on SimpleBench and placing fifth, well behind expectations. Users have pointed out that earlier models like GPT-4.5 or even smaller variants outperformed it in key areas, raising questions about the true nature of AI progress.
What Users Are Actually Experiencing
The complaints are remarkably consistent across platforms. Users report “short replies that are insufficient, more obnoxious AI-stylized talking, less ‘personality’ and way less prompts allowed with plus users hitting limits in an hour”. Many agree that “answers are shorter and, so far, not any better than previous models. Combine that with more restrictive usage, and it feels like a downgrade branded as the new hotness”.
Perhaps most concerning for businesses, the personality that once made ChatGPT feel “human-ish” is gone. What used to be witty and warm now feels like a bland corporate memo. This shift matters more than it might seem—conversational AI’s effectiveness often depends on user engagement and trust.
The Technical Reality Check
Noah Giansiracusa, an associate professor of mathematics at Bentley University, described the launch as “underwhelming.” While there were “some improvements,” he said, “they were much more marginal than I would’ve hoped”. The model still struggles with fundamental tasks:
- Math reasoning: Still makes simple mistakes with only minor gains over GPT-4 and needs prompting to get hard problems right
- Logic puzzles: Scored poorly on ARC puzzles, worse than models like Grok 4 on general reasoning puzzles
- Basic comprehension: Continues to make up information and trip over simple math and spelling questions
The Cost of Putting All Eggs in One Basket
OpenAI made a controversial decision that directly impacts business users: the company has chosen to deprecate all preceding models, announcing that all other models would be shut down. For businesses that relied on specific model variants for particular tasks, this creates immediate operational challenges.
ChatGPT Plus subscribers now face limitations with the new GPT-5 Thinking model restricted to 200 messages per week, and no longer have access to the wide variety of AI models that used to be available. This represents a significant reduction in functionality for paying customers—exactly the kind of vendor lock-in risk that smart businesses should avoid.
The Diminishing Returns Reality
Power users have been strikingly underwhelmed with the new tool, raising questions about diminishing returns as the industry spends ever-increasing sums on talent and infrastructure. The prediction markets reflect this disappointment: Google has now overtaken OpenAI in bets about which company will have the best model at the end of August.
This isn’t necessarily bad news for businesses. It suggests the AI landscape is maturing beyond the era of dramatic leaps, moving toward incremental improvements and specialization. As one user noted, “the race has never been as close as it is now”, indicating increased competition and choice in the market.
Why Multi-Model Strategies Make Sense
The GPT-5 launch illustrates why businesses need diverse AI model access rather than dependence on a single provider. The mixed reception, with steps forward and steps back, suggests OpenAI may be prioritizing cost-efficiency over raw capability, as running large language models is notoriously energy-intensive.
Smart businesses are already hedging their bets. Different benchmarks show varying results—while GPT-5 tops some leaderboards, ARC-AGI-2 puts GPT-5 behind the latest version of Grok from Elon Musk’s xAI. This performance variability across different tasks reinforces the value of having multiple models available for different use cases.
The Business Implications
In the absence of definitive assessments, AI model comparisons sometimes come down to “vibes,” and with nearly 700 million people using ChatGPT weekly, opinions vary widely. For businesses, this subjectivity makes standardizing on a single model risky.
The controversy also highlights cost considerations. Users suspect “OpenAI shrinkflation,” with Altman acknowledging that GPT-5 prioritizes “real-world utility and mass accessibility/affordability” over pure capability. This suggests businesses may benefit more from cost-effective model combinations than from premium single-model subscriptions.
A Unified Approach to AI Model Management
The GPT-5 situation perfectly demonstrates why businesses need platforms that provide access to multiple AI models from different vendors. When one model disappoints or changes unexpectedly, teams with diverse model access can quickly pivot to alternatives that better serve their specific needs.
Moreover, it takes longer than a day to gauge the value of a new AI system in professional applications. Having the flexibility to test and compare models side-by-side enables more informed decisions about which tools work best for specific business processes.
The transparent, pay-as-you-go pricing model becomes especially valuable when model performance varies unpredictably. Instead of being locked into subscriptions for underwhelming updates, businesses can allocate their AI budgets based on actual value delivered.
Looking Forward: Realistic Expectations
While Altman called GPT-5 “a significant step along the path to AGI,” he also acknowledged it makes no claims to being AGI, noting “This is not a model that continuously learns as it’s deployed from the new things it finds”. This honest assessment suggests the industry may be moving toward more realistic expectations about AI progress.
For businesses, this means focusing less on chasing the latest model releases and more on building sustainable AI strategies. The GPT-5 reception shows that incremental improvements, not revolutionary leaps, will likely characterize the next phase of AI development.
The Strategic Advantage of Choice
The mixed GPT-5 launch offers an important lesson: in a rapidly evolving AI landscape, flexibility trumps vendor loyalty. Businesses that maintain access to multiple models, transparent pricing, and the ability to switch between providers will be better positioned to navigate the inevitable ups and downs of AI development cycles.
Rather than viewing GPT-5’s underwhelming reception as a setback, forward-thinking businesses can see it as validation of a multi-model strategy. The future belongs to organizations that can quickly adapt their AI tools to match their evolving needs, not those locked into single-vendor relationships with unpredictable update cycles.
As the AI industry matures beyond the era of dramatic breakthroughs, the real competitive advantage will come from smart tool selection, cost management, and the flexibility to evolve with the technology—rather than being at the mercy of any single model’s performance on launch day.
Don’t let your business get caught off-guard by disappointing model updates or sudden vendor changes. StickyPrompts gives you the power to access multiple AI models from different providers through one unified interface, so you’re never locked into a single vendor’s roadmap.