X402 Cloud AI Inference – Gemini 3.1 Pro Text Generation

x402

X402 Cloud AI Inference – Gemini 3.1 Pro Text Generation is a paid API for AI agents from api.x402cloud.space, paid per call via x402, $0.01229/call, status unknown (last checked 2026-10-02).

Runs a pay-per-call USDC text inference request against Gemini 3.1 Pro via the x402 micropayment protocol, returning generated text candidates

Price / call$0.01229

Seller volume →—

Success—

StatusUnknown

How this service works

X402 Cloud AI Inference Endpoints is an agent-ready x402 API provider for Gemini, image, audio, video, realtime, and specialized AI inference workflows. We expose pay-per-call USDC endpoints designed for autonomous AI agents, application backends, trading bots, creative automation, and RAG systems with some of the lowest x402 AI inference prices available in the market.

Output

A JSON object containing a candidates array with the generated text parts nested under content.parts[].text, plus a usageMetadata object with token consumption details. Follows the standard Gemini generateContent response shape.

Example use cases

Example prompt

“Using the x402 Gemini 3.1 Pro inference endpoint, generate a 300-word product description for a noise-cancelling Bluetooth headset — keep the tone professional and limit the output to 512 tokens.”

Technical details

Endpoint

POSThttps://api.x402cloud.space/gemini-3.1-pro?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need pay-per-call Gemini 3.1 Pro text generation billed in USDC via the x402 protocol — ideal for autonomous AI agents, RAG pipelines, or automation workflows that need to avoid monthly subscription commitments and pay only for actual inference calls. Prefer this over direct Gemini API access when you need x402-native micropayment integration.

Side effects

402 Payment Required if the x402 payment header is missing or the USDC balance is insufficient
400 Bad Request if neither prompt nor contents is provided, or if maxOutputTokens exceeds 8192
429 Rate Limit if too many concurrent calls are made
503 or timeout if the upstream Gemini model is unavailable
Empty candidates array if the model produces no output due to safety filters

Input

{
  "prompt": "Write a brief explanation of how machine learning models work in simple terms for a beginner audience.",
  "maxOutputTokens": 256
}

Output

{
  "candidates": [
    {
      "content": {
        "role": "model"
      },
      "finishReason": "MAX_TOKENS"
    }
  ],
  "createTime": "2026-06-18T06:34:34.407364Z",
  "responseId": "epEzasTuGKDP7rcPz7v4wAo",
  "modelVersion": "gemini-3.1-pro-preview",
  "usageMetadata": {
    "trafficType": "ON_DEMAND",
    "totalTokenCount": 270,
    "promptTokenCount": 18,
    "thoughtsTokenCount": 242,
    "promptTokensDetails": [
      {
        "modality": "TEXT",
        "tokenCount": 18
      }
    ],
    "candidatesTokenCount": 10,
    "candidatesTokensDetails": [
      {
        "modality": "TEXT",
        "tokenCount": 10
      }
    ]
  }
}

Schema · Response

{
  "type": "json",
  "example": {
    "candidates": [
      {
        "content": {
          "parts": [
            {
              "text": "Generated response"
            }
          ]
        }
      }
    ]
  },
  "outputSchema": {
    "type": "object",
    "properties": {
      "candidates": {
        "type": "array"
      },
      "usageMetadata": {
        "type": "object"
      }
    }
  }
}

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