I upgraded my Claude token counter tool to compare different models and Opus 4.7 does appear to use 1.46x times the tokens for text and up to 3x the tokens for images - it's priced the same as Opus 4.6 on a per-token basis so this is actually a pretty big price bump https://t.co/PPGrwHf39D
Simon Willison Finds Claude Opus 4.7 Tokenizer Raises Real API Costs
· Updated
Simon Willison, creator of Datasette, updated his token counter tool to compare the new
Opus 4.7 against Opus 4.6. His testing revealed that the model uses 1.46x more tokens for raw text and up to 3x more for images. A 30-page PDF test showed a smaller 1.08x increase.- Text token multiplier
- 1.46x
- Image token multiplier
- Up to 3x
- PDF token multiplier
- 1.08x
- Models compared
- Opus 4.7 vs Opus 4.6
- Analysis tool
- Claude Token Counter
This finding highlights a hidden price hike for API users. Although Anthropic maintained static per-token rates, the increased token volume raises total costs. This is the opposite of the tiered cost-saving approach seen at Google, illustrating a divergence in how labs manage high-reasoning model economics.
Developers should recalibrate API budgets for this inflation when migrating to the recently released Opus 4.7. While Anthropic increased subscriber rate limits to offset costs for chat users, API developers must use Simon's tool to estimate the impact, as PDF results showed much lower inflation.
Simon Willison
@simonw
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View on XStill wondering? A few quick answers below.
Simon Willison discovered that Claude Opus 4.7 uses significantly more tokens than Opus 4.6 for the same input. His testing showed a 1.46x increase for text and up to 3x for images. This means that even though the price per token is the same, the actual cost to process data has increased.
The cost increase is caused by token inflation, where the model's tokenizer breaks text and images into more numerical units than before. Since Anthropic bills per token, using 1.46 times more tokens for the same text results in a 46 percent price hike for API users despite the static per-token rate.
Developers should use Simon Willison's token counter tool to estimate the specific impact on their data types. While text and images see high inflation, text-heavy PDFs showed a much lower 1.08x increase. Recalibrating API budgets is essential before migrating production workflows to the new model to avoid unexpected billing spikes.




