Recently, a new term has sparked widespread discussion: "Tokenpocalypse."
The reason is Microsoft's pricing overhaul of GitHub Copilot. Starting June 1, Copilot fully transitioned to a token-based billing model, with vastly different token cost multipliers across models—some models charge up to 60 times more per token than others.
And the advanced models that users consistently regard as “truly useful” are precisely the ones with the most dramatic price increases.
As leading AI companies such as Anthropic and OpenAI prepare for IPOs, AI companies will face increased pressure to become profitable, potentially forcing more vendors to follow suit with price increases.
The cost of using AI is an inevitable challenge in expanding corporate productivity. The recent trend of "tokenmaxxing," which drove employees to compete on token usage, will come to an end as the token deadline approaches.
The entire tokenmaxxxing trend, from its rise to its peak and then to rejection, lasted only six months.
The enterprise's dilemma
A developer from a large company described an absurd situation: the company has long mandated that employees use AI tools, and using too few tokens would result in a reprimand. But with the new pricing, using too many tokens now also leads to a reprimand.
Even more critically, the Copilot team has yet to launch the "employee-level token limit" feature. This means that, under the new billing model, a single employee could exhaust the entire company’s monthly token budget in one day.
“My job is no longer about using software to solve business problems,” the developer wrote. “My job has become about solving token usage issues.”
The comments section is even more entertaining. One user summed it up: “The company policy has become: 'Use AI for everything, but be careful not to use it too much—because if the LLM consumes too many tokens, you’ll get suspended, and then you’ll be criticized for not using AI for the rest of the month.'”
Companies that overly emphasize AI productivity may also be wielding a double-edged sword.
An information officer from a major law firm even “bragged” at an AI seminar that after their AI system went down, lawyers essentially stopped working because they had become completely dependent on AI.
A person trained professionally for years freely admits they can’t work without an AI chatbox? I’d be so ashamed that I’d start questioning my entire career.
Uber Overspending Incident: A Microcosm of the Industry
Most AI models today come with usage packages, and as token pricing gradually shifts to pay-as-you-go, enterprises are facing increasingly serious challenges in budget control.
In a little over a month and a half, Uber completed a full cycle: first discovering that its AI spending was burning through budgets much faster than expected, then urgently implementing usage caps and employee restrictions.
"Imagine that even companies like Uber, which heavily rely on AI, are hitting walls so quickly," discussed on the TechCrunch podcast. "The question is: Can AI labs reduce costs to align with what customers are willing to pay?"
A little-known fact: When ChatGPT Plus was first priced at $20 per month, there was no strategic reasoning behind it—it was just a number pulled out of thin air. The entire industry is still paying the price for that starting point.
Your job won't be replaced by AI, but your budget might be.
There are more intriguing details on Reddit. Someone set up an AWS Bedrock cost monitoring dashboard that real-time streams the spending for each model and each token—including cached tokens—to CloudWatch, “letting developers and finance teams watch the money burn.” The comments reacted: “Congratulations, you’ve just given them a new KPI.”
Another major company experienced a similar cutback: after exhausting their AI quota, everyone was forcibly downgraded to GPT-4.2, losing even VSCode integration.
An outsider from outside the tech industry voiced what many are thinking: “The amount of mental energy and actual hours consumed by all of this has already impacted the delivery of work that truly helps the company make money.”
While the entire industry remains immersed in the narrative that "AI will replace everything," a more realistic issue has emerged: someone ultimately has to pay the bill for compute power. And the "Token Apocalypse" may merely be the beginning of this reckoning.