TOKEN ECONOMY
What the tokens cost, and where they went
Every connected account, by model and by day — input, cached and output tokens against the price list, plus what none of it could account for.
Model cost
$101,200
Total tokens
64.49B
Cached input
23%
Cost per 1M tokens
$1.57
Models in use
9
Accounts reading
4
Waiting on you
2 accounts cannot proceed. $12,250/month is on the bill and unreadable in the logs.
Token economy
Where the tokens go, and what each one costs
Token usage by day
Same data, four ways to cut it
Cache effectiveness
Cached share against cost per million — bubble size is volume
Caching is the one lever that lowers cost without touching the model or the output. A model sitting high and left is paying full rate on input it has seen before.
Evidence behind these figures
How the $101,200 above was arrived at
token counts read straight from your provider's logs — the bulk of any bill
computed where coverage left a gap, from the rates beside it
the sampled traffic a completed run actually replayed and observed
These three account for the whole window. Nothing here is assumed — every figure on this page was either read, replayed, or computed from something that was.
What is missing · monthly rate
- Unattributed$33,125
- Spend inside accounts we are connected to, on calls whose logs did not say which application made them. We know the amount; we do not know the owner. It is what 72% coverage leaves behind — closing it means better log labelling at the source, not another connector.
- Unread$46,950
- Spend in accounts nothing is connected to. Enumerated and visibly busy, but no connection reads them, so none of it reaches any figure on this page. Connecting them is the fix.
Neither is folded into the totals above, and both are monthly rates — they do not narrow when you shorten the window.
Usage detail
Latest day (2026-08-30) above, whole window below
| Model | RequestsLatest / period | InputLatest / period | CachedLatest / period | OutputLatest / period | TotalLatest / period | CostLatest / period | Rateper 1M |
|---|---|---|---|---|---|---|---|
gemini-2.5-pro Google Vertex AI | 293.1k6.8M | 888.5M16.82B | 157.6M3.73B | 52.8M1.01B | 961.2M18.28B | $1686.34$32,163 | $1.76 |
gpt-4.1 Azure AI Foundry | 139.4k4.1M | 343.1M9.83B | 16.3M557.6M | 20.1M618.4M | 363.3M10.44B | $821.47$23,745 | $2.27 |
claude-sonnet-4-5 Anthropic | 94.4k2.1M | 174.5M5.28B | 51.4M1.71B | 9.7M322.5M | 189.7M5.74B | $610.44$18,152 | $3.16 |
gpt-4.1-ft-vega01 Azure AI Foundry | 48.9k1.9M | 161.7M4.80B | 3.7M117.8M | 8.4M304.9M | 170.1M5.11B | $577.86$17,800 | $3.49 |
gpt-4.1-mini Azure AI Foundry | 87.8k2.9M | 207.7M6.86B | 29.6M937.8M | 11.6M422.3M | 219.3M7.29B | $92.01$3,140 | $0.43 |
gemini-2.5-flash Google Vertex AI | 94.7k3.1M | 235.2M7.39B | 59.7M2.34B | 15.6M425.2M | 250.8M7.81B | $97.37$2,765 | $0.35 |
claude-haiku-4-5 Anthropic | 28.2k1.2M | 72.5M3.07B | 31.5M1.38B | 4.3M187.3M | 76.9M3.26B | $63.35$2,759 | $0.85 |
gemini-2.5-flash-lite Google Vertex AI | 84.0k1.8M | 144.2M4.27B | 86.7M2.24B | 10.9M267.9M | 155.1M4.54B | $12.26$362 | $0.08 |
gpt-4o-mini Azure AI Foundry | 32.1k792.8k | 59.8M1.90B | 20.8M625.2M | 3.2M122.4M | 63.0M2.03B | $11.25$315 | $0.16 |
Cost is derived from token counts against the published price list, so the rate in the last column reconciles with the totals beside it rather than being an average of averages.