Three Token Types, Three Price Points
Modern LLMs accept three input modalities: text, images, and audio. Each is tokenized differently and priced differently. Understanding these differences reveals opportunities to optimize costs by choosing the right modality for each data type.
Text Token Pricing
Text is priced per BPE token. One token is roughly 3.5 characters of English prose, but only 2.5 characters of code or structured data. Pricing ranges from $0.25/M (Haiku) to $15/M (Opus) for input tokens. Text is the most expensive modality per character of content.
Image Token Pricing
Images are priced by tiles (fixed-size pixel blocks). A single tile costs roughly 1,334 tokens at Sonnet pricing. The critical insight: the content inside the tile is irrelevant to the cost. A tile full of dense text costs the same as a tile of a blank gradient. This flat-rate structure creates the visual encoding arbitrage.
The Arbitrage Window
The text-to-image arbitrage exists because AI providers price image tiles based on pixel area, not information content. By packing maximum text into minimum pixel area, you maximize the information-per-token ratio. At current pricing, this yields an 85–89% cost reduction for text-heavy payloads.
Will the Arbitrage Last?
Possibly not forever. Providers may eventually introduce content-aware image pricing or equalize text and image rates. However, as of 2026, no provider has signaled such changes. The structural reason for flat-rate image pricing — it simplifies billing for genuine image analysis use cases — suggests the arbitrage may persist for some time.
Frequently Asked Questions
Conclusion
Visual token encoding is a practical, immediately deployable optimization that works with your existing AI stack. Whether you are a developer building pipelines or a founder managing API budgets, the ~88% input cost reduction compounds into real savings that improve your margins and extend your runway.
Ready to try it? Open PXINK and drop a file to see your savings instantly.