The era of ‘good enough’ AI has arrived

The release of Google’s latest AI models this week at Google I/O was yet another example of the direction of travel for the generative AI revolution. Facing a user base that is increasingly burning more tokens under basic subscriptions or API access, AI companies are starting to hike prices and throttle usage. In response to those cost pressures, consumers are beginning to cut their cloth accordingly. And while frontier AI providers are releasing ever more powerful models into the world, smaller companies are advancing, too. Often based in China, these are frequently accused of copying the innovations of U.S. models through techniques like distillation, or reverse engineering the way artificial intelligence models work by probing them and inferring their answers. What it means is that these slightly less powerful AI models are, despite lagging behind the bleeding edge, still plenty powerful for most people. The 2026 Stanford University AI Index found that AI models’ performance on the SWE-bench Verified coding benchmark surged from 60% to nearly 100% of the human baseline in the last year, while the highest-quality models gained 30 percentage points on the highly difficult Humanity’s Last Exam benchmark. At the same time, Stanford charted a shrinking gap between U.S. models and their Chinese competitors, which are often offered at a fraction of the price, or entirely free through locally hosted versions. The result is that we’re entering the “good enough” era of AI models, where the needs of all but AI’s power users could be capably handled with something that costs less than giving the likes of Anthropic or OpenAI $200 a month. “Not every task requires maximum capability,” says Azeem Azhar, founder of the Exponential View newsletter, and a user of both the frontier models put out by the biggest AI labs and smaller, cheaper alternatives. “You don’t need Nobel scientist intelligence to appeal a parking ticket.” Not everyone agrees that the gap between the cutting edg