I Cut Vision LLM Costs by 98.9% -> Here's How Token0 Works Under the Hood

Every time you send an image to GPT-4o, Claude, or Gemini, you are paying for vision tokens. And most of them are wasted. I built Token0 : an open-source API proxy that sits between your app and the LLM provider, optimizes every image request automatically, and typically saves 70-99% on vision costs. It is now live on PyPI. In this post, I will walk through the problem, the seven optimization strategies, the benchmarks, and how to get started in under a minute. The Problem: Vision Tokens Are Expensive and Poorly Optimized Text token optimization is a solved problem. Prompt caching, compression, smart routing : the tooling is mature. But images : the modality that costs 2-5x more per token have almost no optimization tooling. Here is what happens today: Wasted pixels. You send a 4000x3000 photo to Claude. Claude silently downscales it to 1568px max. You paid for the original resolution. Those tokens are gone. Wrong modality. A screenshot of a document costs ~765 tokens on GPT-4o as an i