The interactive calculator needs JavaScript, which your browser doesn’t support. Here is a representative
worked example instead: a deep-research agent that runs 50 turns and
totals 4.0M cached input reads, 1.5M fresh input tokens, and 250K output
tokens, priced on Sail’s zai-org/GLM-5.1-FP8 and on generic
frontier-class tiers at list prices (Sonnet-class: $3 input / $15 output
/ $0.30 cache reads per 1M tokens; Opus-class: $5 / $25 / $0.50).
| Where it runs | Cost | vs Sail standard |
|---|---|---|
Sail flex | $1.37 | 0.7x |
Sail standard | $1.86 | 1x |
Sail priority | $2.52 | 1.4x |
Sail asap | $4.24 | 2.3x |
| Sonnet-class API, batch tier (24h window) | $4.73 | 2.5x |
| Sonnet-class API | $9.45 | 5.1x |
| Opus-class API | $15.75 | 8.5x |
How the math works
- Fresh input: tokens the model reads for the first time each turn (new tool results, search snippets, file contents).
- Cached input: tokens reread from prompt cache (the growing conversation
history). Cache reads are billed at the
cachedrate. - Output: tokens the model writes (reasoning and answers).
Assumptions and caveats
- Frontier tiers are generic list prices. “Sonnet-class” is $3 input / $0.30 cache reads / $15 output per 1M tokens (batch tier = 50% off inside a 24-hour window); “Opus-class” is $5 / $0.50 / $25.
- The open-model provider pricing row is fetched live, using the current OpenRouter list price
- The model has to do the job. For simplicity, the math assumes you’re using a single frontier-class open model for your task. Often, we see the hybrid approach using both frontier closed models and open models, or a mix of open models.