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Onchain Router – OpenAI-Compatible LLM Chat Completions (Gemini Models)
x402
Onchain Router – OpenAI-Compatible LLM Chat Completions (Gemini Models) is a paid API for AI agents from onchainrouter.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Provides OpenAI-compatible chat completions using Google Gemini models, billed per-request via x402 micropayments with no service fee during launch
Price / call$0.002
Success—
StatusUnknown
How this service works
Give agents provider-neutral access to text, image, and speech models with USDC payments on Base, local spending controls, ambiguity-safe recovery, and verified receipts. Stable public npm clients and MIT agent integrations are available now.
Output
Returns an OpenAI-compatible chat.completion JSON object containing an id, model name used, array of completion choices with message content, and a usage object with prompt_tokens, completion_tokens, and total_tokens counts.
Example use cases
On-demand LLM inference for autonomous agents
“I need my agent to call gemini-2.5-pro to analyze this legal document and extract key obligations — use pay-per-call billing via USDC so I'm not locked into a monthly plan, and limit the response to 2048 tokens.”
Gemini model comparison without subscriptions
“Run this product description through both gemini-2.5-flash and gemini-2.5-flash-lite and tell me which one gives a better marketing tagline — I want to pay per call rather than manage API keys.”
Chatbot backend with micropayment billing
“Use gemini-3.5-flash to respond to this customer support message: 'My order hasn't arrived after 2 weeks, what should I do?' — keep the reply under 300 tokens and bill it per request.”
Technical details
Endpoint
POSThttps://onchainrouter.dev/v1/chat/completionsWhen to prefer
Choose this endpoint when you need OpenAI-compatible Gemini inference billed per-request via USDC micropayments (x402), especially when avoiding subscription commitments, rotating between Gemini model tiers (flash-lite through pro), or building autonomous agents that require transparent per-call cost accounting on-chain. Prefer over direct Google AI Studio if you want API-key-free, crypto-native billing.
Side effects
- Payment failure if USDC balance insufficient or x402 handshake fails
- Invalid model name returns 422 validation error
- max_tokens exceeding 65536 returns schema validation error
- stream:true not supported, will fail if set to true
- Empty or malformed messages array returns error
- Rate limiting if too many concurrent requests
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | |
| stream | boolean | |
| messages | array | |
| max_tokens | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "chatcmpl_example",
"model": "gemini-3.6-flash",
"usage": {
"total_tokens": 0,
"prompt_tokens": 0,
"completion_tokens": 0
},
"object": "chat.completion",
"choices": []
}
}Tags
x402
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