X402 Cloud AI Inference - Gemini Stream Generate Content

x402

X402 Cloud AI Inference - Gemini Stream Generate Content is a paid API for AI agents from api.x402cloud.space, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-26).

Streams AI-generated text responses from Gemini models via pay-per-call USDC micropayment using the x402 protocol

Price / call$0.003

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 streaming JSON response containing an array of candidates, each with content parts holding generated text, plus usageMetadata with token counts. The response mirrors the Gemini generateContent API format.

Example use cases

Example prompt

“Use Gemini via x402Cloud to stream a response to this prompt: 'Explain the concept of zero-knowledge proofs in simple terms' — cap the output at 512 tokens.”

Technical details

Endpoint

POSThttps://api.x402cloud.space/v1beta/models/%7Bmodel_name%7D:streamGenerateContent?utm_source=zero.xyz

When to prefer

Choose this endpoint when your AI agent or backend needs pay-per-call Gemini inference without a Google API subscription, especially in autonomous agent pipelines, trading bots, or RAG systems that benefit from x402 USDC micropayments and streaming output rather than polling.

Side effects

402 Payment Required if USDC payment header is missing or insufficient
Invalid model_name in path returns 404 or 400
Prompt exceeding 32000 characters returns validation error
maxOutputTokens above 8192 returns schema validation error
Empty or missing prompt/contents field returns 400 bad request
Network timeout on long streaming responses

Output

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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