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Stack Facts LLM Model Price Estimator
x402
Stack Facts LLM Model Price Estimator is a paid API for AI agents from g5joilnmeep4ntz3nwezxt5dmu.srv.us, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-13).
Estimates the cost of an LLM API call given a model name and token counts, returning a signed, pay-per-call breakdown in USD
Price / call$0.003
Success—
StatusUnknown
How this service works
Check a package before install: malware, known vulnerabilities (OSV), exploited CVEs (CISA KEV) and end-of-life, plus LLM prices; signed answers, pay per call in USDC, no account or API key.
Output
Returns a signed JSON payload with the model's canonical name, a line-by-line cost breakdown (input, cached, output tokens), total cost in USD and micro-USD, the pricing formula used, deprecation status and date, a SHA-256 hash and cryptographic signature for tamper verification, the data source URL, dataset snapshot ID, licence, and a staleness flag — all reflecting the latest pricing snapshot.
Example use cases
Pre-call cost gate for AI workflow
“Before sending this request to GPT-4o, estimate what it will cost me — I'm planning 2,000 input tokens and 800 output tokens — so I can decide if it's worth it.”
Budget check for high-volume inference
“I'm about to run a batch job using Claude 3.5 Sonnet with roughly 500 input tokens and 1,500 output tokens per call. What's the estimated USD cost per call so I can figure out what 10,000 calls will cost me?”
Comparing cached vs uncached token pricing
“Get me the cost breakdown for calling openai/gpt-4o with 1,000 input tokens where 400 of them are cached and 600 are new, plus 300 output tokens — I want to see how much the caching saves me.”
Technical details
Endpoint
POSThttps://g5joilnmeep4ntz3nwezxt5dmu.srv.us/v1/models/estimate?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a cryptographically signed, verifiable LLM cost estimate on a per-call basis with no API key or account setup — especially suitable for agents that need to gate or log LLM spending, compare model costs programmatically, or audit pricing with a tamper-evident signature. Prefer it over scraping provider pricing pages or using unofficial community spreadsheets when auditability and freshness guarantees matter.
Side effects
- Unknown or misspelled model name returns no matching data or an error
- Token count values exceeding the maximum (10B) are rejected
- Payment in USDC not submitted or insufficient causes HTTP 402 before any data is returned
- Stale pricing snapshot may cause meta.stale=true flag if data hasn't been refreshed
- Sources disagreeing on a price field triggers a sources_disagree array warning rather than a hard error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | |
| input_tokens | integer | |
| cached_tokens | integer | |
| output_tokens | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"name": "GPT-4o",
"lines": [
{
"kind": "input",
"tokens": 1000,
"cost_usd": "0.002",
"price_field": "input_usd_per_mtok",
"usd_per_mtok": 2
}
],
"model": "openai/gpt-4o",
"notes": [],
"formula": "cost_usd = (input_tokens × inpu…",
"cost_usd": "0.004",
"deprecated": false,
"cost_micro_usd": 4000,
"deprecation_date": null,
"sources_disagree": [
"input_usd_per_mtok"
],
"days_until_deprecation": null
},
"meta": {
"as_of": "2026-10-09T06:00:00Z",
"stale": false,
"key_id": "sf-test-1",
"notice": "Normalised (modified) from the …",
"sha256": "f99d55c9aa420561de698d63d70d916…",
"source": "https://raw.githubusercontent.c…",
"dataset": "models",
"licence": "MIT",
"signature": "AvlI5FXM8fD9oncZAr9velQseOBO9X7…",
"attribution": "Pricing data derived from LiteL…",
"snapshot_id": "models-20261009T060000Z-f99d55c9",
"manifest_url": "/v1/models/manifest",
"retrieved_at": "2026-10-09T06:00:00.000Z"
}
}
}Tags
x402
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