The Opus 4.7 Tokenizer Tax

Anthropic quietly raised Opus prices by changing the tokenizer, not the price tag. Here's what it actually costs when measured across 17K real-world Claude Code users.

We’ve all had a few weeks to sit with Opus 4.7, and consensus is that Anthropic just raised the price of Opus as much as ~40% without changing the price tag.

The nominal per-token rate is identical to Opus 4.6 ($5/$25 per million), but a new tokenizer maps the same input to more tokens. Anthropic’s own stated range was 1.0-1.35x, but others such as Simon Willison are reporting inflation at levels up to 46%. (He saw this, for example, on the model’s own system prompt.)

Same prompt + same words → bigger bill.

Tomasz Tunguz framed this well in his recent newsletter: smarter models used to be cheaper per outcome. Opus 4.5 needed 76% fewer tokens than Sonnet to reach the same result, making it 60% cheaper despite a higher sticker price. Opus 4.7 reverses the pattern. He calls it a sawtooth: resolution goes up and cost goes up, then efficiency gains bring it back down. Rinse and repeat. The net effect across each cycle is more tokens consumed industrywide.

This connects directly to the data we’ve been tracking at Jellyfish. Recently I shared data showing 10x token cost for ~2x throughput at the highest usage decile... and that exponential cost curve just got steeper. If your heaviest AI users were already in the $90/PR range, they may have quietly crossed into $125+ territory in the last week without writing a single line of code differently.

So what has the tokenizer tax turned out to be in reality? Our current estimate: 17%

What’s going on? First, note that input tokens are just part of the equation. In practice, the real costs depend on how much you use Claude Code, the proportion of extended thinking (since input tokens are proportionally less of the total as thinking time increases), and the type of work you do. (For example, perhaps Opus 4.7 works more efficiently, resulting in fewer tokens overall?)

To sort this out, we took a look at Jellyfish data across 17K Claude Code users who switched from Opus 4.6 to 4.7. Using a statistical model to control for individual differences in the type and amount of work across developers, we saw that switching to 4.7 was associated with a 17% increase on average, with this “tax rate” decreasing as thinking time increases (and increasing as thinking decreases).

The chart above illustrates what this looks like for three scenarios, based on level of Claude Code token consumption: low (bottom 20%), median, and high (top 20%). These figures represent typical levels of weekly usage cost, proportion of extended thinking, and total expected change due to switching from Opus 4.6 to 4.7.

The headline: the tokenizer tax is real and significant, but also less than half what you’d estimate from first principles. It’s a good reminder that these systems are complex, and each engineering team’s use cases are unique – the only reliable way to know the actual cost impact is to measure it yourself.