Tokenomics
Pricing designed for production workloads
What’s inside
What’s hidden inside the token?
AI platforms charge for tokens because tokens roughly represent computation. It bundles model usage with cloud overhead, infrastructure margins, and licensing costs. Radium strips the token down to what actually matters, so you pay for intelligence, not inefficiency.
Switching from OpenAI or Anthropic.
Compare
Token Comparison
Tokens look simple, but inside them lives a stack of cloud costs, infrastructure margins, and licensing layers.
Understanding Tokens
Most infrastructure leaves
GPU capacity unused
Traditional inference systems often underutilize GPU capacity due to fragmented routing, idle cycles, and inefficient execution. This means fewer tokens are produced from the same hardware.
Rewriting the token
Radium has optimized
token througput on our GPUs
Radium optimizes routing, batching, and execution across the delivery stack. By keeping GPUs consistently utilized, Radium increases the amount of output produced from the same infrastructure.
Technology Page
Resources
Resources for teams evaluating, integrating, and operating Radium
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Get Started
One line of code to switch.
A different class of performance.
Swap OpenAI for Radium in your API call. That's it.
