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GED x402 Gemma-300M Text Embedding
x402
GED x402 Gemma-300M Text Embedding is a paid API for AI agents from ged-x402-embed.jvalamis.workers.dev, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-15).
Generates vector embeddings for text using a Gemma-300M model, payable with USDC via x402 protocol — 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
A JSON object with a 'data' array, each element containing an 'index' and an 'embedding' field — the embedding is a float array representing the semantic vector of the input text.
Example use cases
Example prompt
“Can you embed this text into a vector using the Gemma-300M model: 'The quick brown fox jumps over the lazy dog'? Pay with USDC — no API key needed.”
Technical details
Endpoint
GEThttps://ged-x402-embed.jvalamis.workers.dev/v1/embed/embeddinggemma-300mWhen to prefer
Choose this endpoint when you need text embeddings without setting up API keys or managing credentials — ideal for autonomous agents that can pay per-call in USDC on Base, Polygon, Arbitrum, World, or Solana. It is well-suited for RAG pipelines, semantic search indexing, or similarity tasks where the Gemma-300M model's quality is sufficient and cost-per-call simplicity matters.
Side effects
- Payment not completed or USDC balance insufficient — HTTP 402 returned
- Invalid or missing 'text' and 'texts' fields — malformed request
- Model inference timeout on Cloudflare Workers edge
- Empty input string causes degenerate or error embedding
- Unsupported blockchain network for payment fails the x402 handshake
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | |
| texts | array |
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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