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PennyRail LLM Mini Inference
x402
PennyRail LLM Mini Inference is a paid API for AI agents from pennyrail.vercel.app, paid per call via x402, $0.01/call, status down (last checked 2026-10-30).
Runs a mini LLM inference call via a pay-per-use settlement endpoint, returning a language model response for a given input.
Price / call$0.01
Success—
StatusDown
How this service works
Machine-readable settlement service
Output
Returns a JSON object containing the LLM inference output — typically the generated text or model response corresponding to the provided input payload. The response schema is open-ended (additionalProperties: true), so the exact shape depends on the model's output format.
Example use cases
Cheap per-call AI text completion
“I need to generate a one-sentence product description for a new coffee mug using a lightweight, pay-per-use LLM — just send it the product name 'Morning Bloom Mug' and get back a short description.”
Automated micro-task text generation
“For each of these 10 support tickets, I want to use the mini LLM to draft a one-line reply — process this ticket: 'My order hasn't arrived after 2 weeks, what should I do?'”
Low-cost prompt testing pipeline
“I'm experimenting with prompts and want to test this one cheaply: 'Explain the concept of compound interest in one sentence as if I'm 10 years old.' Run it through the mini LLM and show me the result.”
Technical details
Endpoint
POSThttps://pennyrail.vercel.app/api/p/standard/ai.llm-mini--llm-inference?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a low-cost, per-call LLM inference with micro-payment settlement via the x402 protocol and USDC. It is ideal for high-volume, cost-sensitive pipelines where paying $0.01 per call is preferable to subscription models. Best suited for lightweight inference tasks where a 'mini' model is sufficient. Not ideal for complex, long-context reasoning tasks that require a full-scale LLM.
Side effects
- Payment failure (insufficient USDC or x402 handshake error) — returns 402 Payment Required
- Malformed input object — returns 400 Bad Request if required 'input' field is missing
- Model unavailability or timeout — returns 503 or 504 if the underlying mini LLM backend is down
- Empty or ambiguous input object — may return a low-quality or empty inference result
- Rate limiting — may return 429 if too many calls are made in a short period
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
Reviews
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