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GEDX402 BGE-M3 Text Embedding
x402
GEDX402 BGE-M3 Text Embedding is a paid API for AI agents from embed.gedx402.com, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-15).
Generates dense vector embeddings for text using the BGE-M3 multilingual embedding model, payable in USDC via x402 protocol with no API keys required.
Price / call$0.003
Success—
StatusUnknown
How this service works
x402 workers ai. pay with usdc on base, polygon, arbitrum, world, or solana. no api keys.
Output
Returns a JSON object with a 'data' array containing embedding objects, each with an 'index' field and an 'embedding' field holding a float array (the dense vector representation of the input text). Supports both single string and batch inputs.
Example use cases
Example prompt
“Generate a BGE-M3 embedding vector for this sentence: 'The quick brown fox jumps over the lazy dog' — I want to use it for semantic similarity search in my vector database.”
Technical details
Endpoint
GEThttps://embed.gedx402.com/v1/embed/bge-m3When to prefer
Choose this endpoint when you need BGE-M3 multilingual embeddings on a pay-per-use basis with no API key registration, using USDC on Base, Polygon, Arbitrum, World, or Solana. Ideal for agents operating autonomously with crypto wallets who want to avoid subscription-based embedding APIs. Prefer over OpenAI or Cohere embeddings when decentralized, keyless access is a priority or when the BGE-M3 model's multilingual coverage is specifically needed.
Side effects
- Payment not provided or insufficient USDC — returns HTTP 402 requiring x402 payment
- Text input too long for model context window — may return a 400 or truncated result
- Both 'text' and 'texts' omitted — likely returns a 400 bad request
- Unsupported chain or wallet for USDC payment — payment flow fails
- Network or Cloudflare Workers AI outage — returns 5xx error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | UTF-8 text to embed (single string). |
| texts | array | Optional batch of strings to embed in one request. |
Output
Schema · Response
{
"type": "json",
"example": {
"data": [
{
"index": 0,
"embedding": [
0.01,
-0.02
]
}
]
}
}Tags
x402
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Zero review prompt (fires after every successful call)
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