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Grokzilla LLM Cost Quote
x402
Grokzilla LLM Cost Quote is a paid API for AI agents from grokzilla.shop, paid per call via x402, $0.0034/call, status unknown (last checked 2026-10-27).
Estimates the cost of running a prompt across LLM models by looking up OpenRouter's live price list, returning models ranked cheapest first with a price-fetched-at timestamp.
Price / call$0.0034
Success—
StatusUnknown
How this service works
Text or token counts in, cost per model out, cheapest first, from OpenRouter's public price list with a price-fetched-at timestamp. Applies time-of-day pricing. Not charged if the price list is unavailable or no model matches.
Output
A list of LLM models ranked cheapest first, each with its cost estimate for the given input text or token counts, plus a price-fetched-at timestamp reflecting when OpenRouter's price list was retrieved. Time-of-day pricing adjustments are applied. If the price list is unavailable or no models match, no charge is incurred and an appropriate response is returned.
Example use cases
Pre-flight LLM cost check
“Before I run my batch job, can you get me price quotes for sending this 2000-word document through the 10 cheapest models on OpenRouter with 500 output tokens? I want to know which one is most cost-effective.”
Budget-constrained model selection
“I've got a tight budget. What are the top 3 cheapest models on OpenRouter for a prompt that's about 1500 input tokens and 300 output tokens? Include free models too.”
Dynamic cost comparison for agent routing
“My agent needs to pick a model for each task at runtime. Can you quote me the cost for this text across the 25 cheapest OpenRouter models with 500 output tokens so I can route to the best value option?”
Technical details
Endpoint
POSThttps://grokzilla.shop/api/skills/llm-cost-quote?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need real-time LLM pricing data from OpenRouter to make cost-aware model selection decisions, especially when comparing multiple models before committing to an API call. Prefer it over hardcoded pricing tables when you need up-to-date prices with time-of-day adjustments. It's ideal for agents that route tasks to models dynamically based on cost constraints.
Side effects
- OpenRouter price list unavailable — returns error, no charge applied
- No models match the specified filter — returns empty result, no charge applied
- text exceeds 400,000 character limit — validation error
- input_tokens or output_tokens out of allowed range — validation error
- models array exceeds 25 items — validation error
- top parameter outside 1–50 range — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| top | integer | |
| text | string | |
| models | array | |
| request_id | string | Optional idempotency key. Echoed back; a credit-pack redemption with the same request_id and body is charged once. |
| include_free | boolean | |
| input_tokens | integer | |
| output_tokens | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"data": {
"quotes": [
{
"name": "OpenAI: GPT-4o-mini",
"model": "openai/gpt-4o-mini",
"cost_usd": "0.00069",
"fits_context": true,
"context_length": 128000,
"time_based_price": false,
"input_usd_per_mtok": "0.15",
"output_usd_per_mtok": "0.6"
},
{
"name": "Google: Gemini 2.5 Flash",
"model": "google/gemini-2.5-flash",
"cost_usd": "0.0019",
"fits_context": true,
"context_length": 1048576,
"time_based_price": false,
"input_usd_per_mtok": "0.3",
"output_usd_per_mtok": "2.5"
}
],
"currency": "USD",
"input_tokens": 3000,
"token_source": "caller-supplied input_tokens",
"output_tokens": 400,
"missing_models": [],
"price_fetched_at": "2026-10-17T11:12:57Z",
"models_considered": 2
},
"next": [
"token_count"
],
"skill": "llm_cost_quote",
"charged": true,
"service": "llm_cost_quote",
"sources": [
{
"url": "https://openrouter.ai/api/v1/models",
"name": "OpenRouter public models list",
"fetched_at": "2026-10-17T11:12:57Z"
}
],
"summary": "cheapest: openai/gpt-4o-mini $0.00069 for 3000 in + 400 out tokens",
"version": "1.0.0",
"warnings": [],
"confidence": 0.97,
"data_as_of": "2026-10-17T11:12:57Z",
"generated_at": "2026-10-17T11:12:57Z"
}
}Tags
x402
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