Anthropic's prompt caching is powerful, but it's not the only way to save money on large context windows. See how PXINK's visual encoding compares.
Start Optimizing for Free| Feature | PXINK (Visual Encoding) | Prompt Caching (Anthropic) |
|---|---|---|
| Primary Mechanism | Converts text to dense pixel images | Caches prefix tokens server-side |
| Cost Savings | ~88.5% on every single API call | Up to 90%, but only on subsequent identical calls |
| Best For | Highly dynamic context (e.g. changing logs, new code) | Static context (e.g. fixed system prompts, big rulebooks) |
| Cold Start Cost | Very Low (Tokens are always compressed) | High (Initial request pays 1.25x base token cost) |
| Model Support | Claude Sonnet 4.6, GPT-5.6, Gemini 3.1 Pro / 3.5 Flash | Claude only (API specific) |
The Verdict: If your context changes frequently (like pasting in different code files for review), PXINK's visual encoding is vastly cheaper because you never pay the "cache write" penalty. If your context is completely static (like a 50-page company handbook), prompt caching is the way to go. Better yet? Use them together.
Yes. You can encode your dynamic text (like code or logs) as an image using PXINK, and use prompt caching for your static system instructions. This hybrid approach yields the absolute lowest API bill possible.
Because PXINK uses deterministic 5x8 bitmap fonts without anti-aliasing, modern vision models (like Claude Sonnet 4.6) read the text with near 100% OCR accuracy. Reasoning remains incredibly sharp.