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Synap Chat Completions — OpenAI-compatible Inference API
x402
Synap Chat Completions — OpenAI-compatible Inference API is a paid API for AI agents from synap.linkrra.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-23).
Runs LLM chat completions using Qwen3-Coder-30B via an OpenAI-compatible endpoint with zero data retention and per-call micropayment via x402
Price / call$0.001
Success—
StatusUnknown
How this service works
AI powered by the people, for the people. OpenAI-compatible inference API with zero data retention — qwen3-coder-30b at $0.0675/1M in, $0.27/1M out. Contribute your GPU, earn credits.
Output
Returns an OpenAI-style chat.completion JSON object including the assistant's reply message, token usage breakdown (prompt, completion, total), and a payment confirmation object with the Base network transaction hash and amount paid in USD.
Example use cases
Code generation via community GPU inference
“Use the Synap community inference API to generate a TypeScript function that validates an email address — system prompt is 'You are an expert TypeScript developer', user message is 'Write a regex-based email validator function with tests.'”
Privacy-first AI assistant response
“I need a zero-data-retention LLM response from Synap — system prompt is 'You are a confidential legal summarizer', user message is 'Summarize the key obligations in this contract clause: The licensee shall not sublicense...'”
Low-cost automated text pipeline
“Hit the Synap inference endpoint to classify the sentiment of this customer review and return a JSON label — system prompt is 'You are a sentiment classifier. Respond only in JSON.', user message is 'The product arrived late and the packaging was damaged, though the item itself works fine.'”
Technical details
Endpoint
POSThttps://synap.linkrra.com/v1/chat/completions?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a low-cost, OpenAI-compatible LLM inference API with strict zero data retention guarantees, are comfortable with micropayment-per-call billing via x402 on Base, and want to leverage a community GPU network running Qwen3-Coder-30B — particularly suited for code generation, reasoning tasks, or privacy-sensitive workloads where retaining user data on a provider's servers is unacceptable.
Side effects
- Payment failure if insufficient USDC balance — returns 402 Payment Required
- Model overload or GPU unavailability from community network — may return 503 or timeout
- Malformed request body not matching OpenAI schema — returns 400 with validation error
- Network latency spikes due to distributed GPU sourcing
- Rate limiting if too many concurrent requests
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | "auto" = cheapest of our self-hosted models that fits, or name one. |
| stream | boolean | true = stream OpenAI-format Server-Sent Events. |
| messages | array | OpenAI-format chat history, oldest first: [{role, content}]. |
| max_tokens | integer | Completion token cap. The price is quoted for the prompt plus this cap. |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "chatcmpl-...",
"usage": {
"total_tokens": 0,
"prompt_tokens": 0,
"completion_tokens": 0
},
"object": "chat.completion",
"choices": [
{
"message": {
"role": "assistant",
"content": "..."
}
}
],
"payment": {
"network": "eip155:8453",
"paidUsd": 0,
"transaction": "0x..."
}
}
}Tags
x402
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