What is each feature
actually costing you?

Add your LLM-powered features, set call volume, pick your model. See where your AI budget is going — and which feature is eating it.

Free · no signup required
Anthropic · OpenAI · Gemini · xAI
Estimates only — track real costs with the SDK
Your features
500/day
200/day
1,000/day
Model
Input$3 / 1M tokens
Output$15 / 1M tokens
Context & ratio
Avg tokens / call
4,000
Input / output ratio
70% / 30%
Wasted spend
Estimated error rate
8%

Calls that error, time out, or return empty output — you still pay for the tokens.

Total calls
51,000
1,700 / day across 3 features
Wasted (8% errors)
$107.71
4,080 calls returning nothing
Cost by feature
30-day · Claude Sonnet 4.6
chat
$792.00
59% · 30,000 calls
search
$396.00
29% · 15,000 calls
summarize
$158.40
12% · 6,000 calls
Cost variance detected

chat costs 5.0× more than summarize over 30 days. This kind of variance is invisible in your API bill — it's exactly what LLM Cost Tracker surfaces automatically, per deploy, in real time.

Estimated wasted spend · 30 days
$107.71

At a 8% error rate, roughly 4,080 calls this month will return nothing — and you'll still be billed for the tokens. LLM Cost Tracker flags these automatically and tells you which feature they're coming from.

This is a projection
See the real numbers — live, by feature, per deploy.

Drop in one SDK call. LLM Cost Tracker starts tracking actual token counts, costs, and wasted spend immediately. No infrastructure. No config beyond wrapping your client.

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