Find the expensive payloads
Group requests by endpoint, model and workflow. Inspect long histories, repeated RAG documents, large tools and retries. Cost per successful user outcome is more useful than an overall average request cost.
Use caching and reduction correctly
Keep stable prefixes consistent for supported prompt caching. Use exact caching for identical deterministic requests. Reduce duplicated or irrelevant dynamic context only when a task-specific quality check passes.
Cost calculator
Enter your current rates and measured average. Nothing is uploaded.
Integrate with minimal changes
OpenAI-compatible clients can change the base URL to Varion and use a Varion key. Customers retain their OpenAI account and provider charges. Varion reports original and provider-bound tokens and can pass through requests unchanged.
Measurement checklist
- Choose a representative completed task, not an artificial one-line prompt.
- Record the selected model, provider input, cached input, output, retries and final result.
- Change one optimization mechanism at a time so the cause remains visible.
- Verify required identifiers, tool calls, code changes or business fields.
- Keep passthrough available when the reduced request does not pass.
How Varion fits
Varion Token Engine is a gateway and testing platform for reducing eligible input-token waste across supported AI traffic. It reports original and provider-bound input, keeps provider charges separate, and does not claim that every request can be reduced. New verified users receive 100,000 processed input tokens and 50 local test runs.
Frequently asked questions
Does Varion lower OpenAI’s published token price?
No. It attempts to reduce eligible provider-bound input and provides separate package pricing for Varion processing.
Does prompt caching already solve everything?
No. Caching can discount repeated eligible prefixes, while context reduction addresses avoidable content and exact caching can avoid identical calls.