Token spend, visible before the invoice.
LLM token costs by model, feature, and request — with baselines that flag drift the day it starts.
- 5 min
- setup, per provider
- 90 days
- history, instantly
- Same-day
- anomaly alerts
- Read-only access
- 14-day free trial
- No credit card required
Daily Spend by Provider
$24,321 total
How does StackSpend handle Token Cost Monitoring?
StackSpend tracks LLM token costs across OpenAI, Anthropic, Claude, Cursor, and other providers, broken down by model, feature, and request. See input vs output token spend, watch cost-per-request trends, get daily signals and anomaly alerts, and forecast token spend before the billing cycle closes.
How does it work in practice?
- 01
StackSpend breaks token spend down by model and provider, separating input and output token cost so the expensive side is obvious.
- 02
Cost per LLM request shows whether prompt size, context length, or retries are moving the number.
- 03
Daily signals, anomaly detection, and pace-to-forecast surface token cost spikes before the invoice lands.
What makes this work?
Every model you run, in one lens.
Usage by base model, project and user, in tokens and in API-equivalent value. Estimated and billed usage stay separate, so the numbers never double-count and never pretend to be your invoice.
Business plan
How it worksEvery dollar has an owner.
Auto-tagging rules label costs as they are ingested, matching provider, account, service and project patterns in priority order. By the time someone asks who owns the spend, the answer is already on the data — filterable and groupable in the explorer.
Team plan and above
How it worksSee this running against your own bill by tomorrow morning.
Read-only · 5 minutes per provider
Who uses this?
- Teams that want daily visibility into spend without manually checking billing portals.
- Buyers replacing spreadsheets and fragmented native dashboards with one monitoring workflow.
- Operators who need read-only setup, alerts, and forecasting before overrun becomes month-end reality.
What does StackSpend track?
- Input and output token spend
- Cost per LLM request
- Token cost by model and provider
- Token spend trends and anomalies
- Pace-to-forecast on token spend
When does this use case fire?
- A prompt or system message grows and token spend climbs across every call
- A retry or agent loop multiplies token usage on a single workflow
- Long-context requests push output token cost far above expectations
- A new AI feature ships with unknown cost per request
Token spend is the largest line in most LLM bills, but provider dashboards report aggregate token counts, not cost by feature or request.
Prompt and context growth inflate token usage silently — a small prompt change can multiply spend across millions of calls.
Without per-model token cost visibility, teams cannot tell whether output tokens, retries, or long context are driving the bill.
How does StackSpend do this?
Provider token usage dashboards is built for different jobs. Here is what StackSpend adds.
Provider token usage dashboards
- Report aggregate token counts, not cost by feature or customer
- No input vs output cost split in one view
- No cost-per-request trend or forecast
- One provider at a time, no cross-provider token view
StackSpend
- Token cost by model and provider in one place
- Input vs output token spend separated
- Cost per LLM request with trend and forecast
- Daily signals and anomaly alerts on token spend
Native tools show you last month. StackSpend tells you tomorrow.
Token Cost Monitoring starts from day one — no manual setup and no threshold tuning required.
Read-only access · Flat plans, never a % of your bill · No credit card required
What do you get when you connect?
- Setup time
- Most teams can connect and validate setup in about 5-10 minutes.
- Access model
- Read-only credentials only. StackSpend does not modify provider resources or billing settings.
- Signals
- Daily Slack or email updates, anomaly alerts, and budget tracking in one workflow.
- History and forecast
- Historical spend context plus pace-to-forecast so overruns are visible before month-end.
Token Cost Monitoring, answered
What is token cost monitoring?
Token cost monitoring tracks the spend your LLM token usage drives — input and output tokens by provider and model, mapped to current model prices — and turns it into a daily cost signal. StackSpend monitors token cost across OpenAI, Anthropic, Claude, Cursor, and Grok, so a prompt change or model switch that doubles token cost is visible the day it happens, not at the invoice.
Why do input and output tokens need to be tracked separately?
Because providers price them differently — across the major providers on our LLM API pricing index, output tokens carry a materially higher per-million rate than input, and cached input is discounted again. A workload that shifts toward longer completions therefore gets more expensive even when total token volume looks flat. StackSpend tracks input, output, and cache behaviour separately so that mix change is visible instead of hidden in a blended number.
How do I keep token cost numbers accurate as model prices change?
That is the hard part of any homegrown tracker: providers change prices and ship new models, and a stale price table silently corrupts every downstream number. StackSpend maintains a cross-provider model price table as part of the product — the same data that powers its public LLM API pricing index — so token-to-cost mapping stays current without anyone owning a spreadsheet.
Can I get an alert when token costs spike?
Yes. Anomaly detection compares each day’s token volume and cost against your baseline and alerts via Slack, email, or webhook the day the pattern breaks — with the provider and model identified, so the fix starts the same day.
How much does token cost monitoring cost?
StackSpend starts with a free 14-day trial (which doubles as a cost health audit of your current spend), then plans from $29/month. Setup is read-only and takes about 5 minutes per provider.
Tomorrow morning: one number, in Slack.
Connect read-only today. Token Cost Monitoring starts from day one — no manual setup, no threshold tuning required.