Text embeddings (Large)

Generate a text embedding vector using OpenAI text-embedding-3-large (3072 dimensions). Higher accuracy than the small model. Ideal for semantic search, RAG, and clustering. No API key needed; pay per call via x402. Text capped at 32k chars.

Input

Example output

{
  "model": "text-embedding-3-large",
  "provider": "openai",
  "embedding": [
    0.0023,
    -0.0091,
    0.0152
  ],
  "dimensions": 3072,
  "usage": {
    "total_tokens": 12
  }
}

Try it - see the 402 challenge (free)

curl -i -X POST https://agent402.tools/api/embed-large \
  -H "Content-Type: application/json" \
  -d '{"text":"Agent402 is an open-source x402 tool server."}'

The response is HTTP 402 Payment Required with exact payment requirements. Any x402 v2 client pays automatically and retries:

Paid call (JavaScript agent)

import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

const client = new x402Client();
registerExactEvmScheme(client, { signer: privateKeyToAccount(KEY) });
const payFetch = wrapFetchWithPayment(fetch, client);

const res = await payFetch("https://agent402.tools/api/embed-large", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    "text": "Agent402 is an open-source x402 tool server."
  }),
});

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