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LLM Gateway – OpenAI-Compatible Chat Completions
x402
LLM Gateway – OpenAI-Compatible Chat Completions is a paid API for AI agents from x402.agentindex.world, paid per call via x402, $0.67584/call, status unknown (last checked 2026-10-02).
Runs non-streaming chat completions against any OpenRouter model via an OpenAI-compatible API, billed per-use via x402 micropayments at 1.10× upstream cost.
Price / call$0.67584
Success—
StatusUnknown
How this service works
OpenAI-compatible chat completions (non-streaming) for any OpenRouter model - GET /v1/models lists them free, with pricing (upstream cost x 1.10). Pay only for what you use: sign a ceiling based on your max_tokens, settle for real usage x 1.10 (min $0.001) once the call completes. Try GET /v1/chat/completions/sample.
Output
Returns an OpenAI-format chat completion object with the model's generated message, finish reason, and token usage stats (prompt tokens, completion tokens, total tokens). Billed at actual token usage × 1.10× upstream model cost, minimum $0.001 per call.
Example use cases
On-demand LLM in agent pipeline
“Use the openai/gpt-4o-mini model to classify this customer support ticket as 'billing', 'technical', or 'general' — limit the response to 100 tokens: 'I was charged twice for my subscription this month and need a refund.'”
Ad-hoc AI answer without subscription
“I don't have an OpenAI account — can you call the anthropic/claude-3-haiku model to answer this question in up to 300 tokens: 'What are the main differences between TCP and UDP protocols?'”
LLM-powered code generation step
“Call google/gemma-3-27b-it with up to 1024 tokens and ask it to write a Python function that parses a JSON list of transactions and returns the total amount spent per category.”
Technical details
Endpoint
GEThttps://x402.agentindex.world/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pay-per-call LLM inference without committing to a subscription, want access to the full OpenRouter model catalog (including open-source and proprietary models), need OpenAI-compatible request/response format for easy drop-in use, or are building an agent that must pay for inference programmatically via x402 micropayments on Base.
Side effects
- Invalid or unknown model ID returns a 400 error
- max_tokens exceeds 4096 cap — clamped or rejected
- Insufficient USDC balance causes x402 payment failure before inference runs
- Malformed messages array (missing role or content) causes validation error
- Upstream OpenRouter model unavailability causes 502/503 response
- x402 payment ceiling mismatch if max_tokens is too low for actual usage
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | OpenRouter model id from GET /v1/models, e.g. "openai/gpt-4o-mini". |
| messages | array | OpenAI-format chat messages: [{role, content}, ...]. |
| max_tokens | integer | Max completion tokens, capped at 4096 - also bounds the x402 upto price ceiling. |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "gen-1790576252-UzfZJjqk0Ld9PGyd1ADA",
"model": "openai/gpt-4o-mini",
"usage": {
"total_tokens": 12,
"prompt_tokens": 10,
"completion_tokens": 2
},
"object": "chat.completion",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "OK."
},
"finish_reason": "stop"
}
],
"x402_receipt": {
"upstream": "llm-gateway",
"latency_ms": 612,
"model_served": "openai/gpt-4o-mini",
"price_paid_usdc": 0.001
}
}
}Tags
x402
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