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Llm Gemini 3 6 Flash

by x402engine.app in AI models & inference

x402 APIPassing, checked 2 h ago

Google's latest fast multimodal model with a 1M-token context window

POST https://x402engine.app/api/llm/gemini-3.6-flash

Last 30 days

All checks passedSome failedAll failedNot checked
Uptime
100%
Response time
235 ms typical, 346 ms slowest 5%
Last check
2 h ago
Next check
any minute now

How to call it

# See the payment challenge (nothing is charged)
curl -i -X POST "https://x402engine.app/api/llm/gemini-3.6-flash" \
  -H "content-type: application/json" \
  -d '{"max_tokens":1024,"messages":[{"content":"Hello","role":"user"}]}'
import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { ExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

const client = new x402Client().register(
  "eip155:8453",
  new ExactEvmScheme(privateKeyToAccount(process.env.AGENT_KEY)),
);
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? Preflight it first for $0.005:
// GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fx402engine.app%2Fapi%2Fllm%2Fgemini-3.6-flash
const res = await pay("https://x402engine.app/api/llm/gemini-3.6-flash", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({"max_tokens":1024,"messages":[{"content":"Hello","role":"user"}]}),
});
console.log(await res.json());

Example input

{
  "max_tokens": 1024,
  "messages": [
    {
      "content": "Hello",
      "role": "user"
    }
  ]
}

Security scan

  • No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

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