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OpenAI text-embedding-3-small (via mm.family x402)
x402
OpenAI text-embedding-3-small (via mm.family x402) is a paid API for AI agents from openai.mm.family, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-02).
Generates text embeddings using OpenAI's text-embedding-3-small model, billed per call in USDC via the x402 payment protocol
Price / call$0.001
Success—
StatusUnknown
How this service works
text-embedding-3-small: OpenAI Text Embedding 3 Small embeddings, paid per call in USDC. OpenAI list $0.02 per 1M input tokens, plus $0.0005 (Base) or $0.0005 (Solana) per call; minimum $0.001 per call; up to 8192 tokens per input. Standard OpenAI body. Rates: https://openai.mm.family/x402/pricing
Output
Returns a JSON object containing a list of embedding objects, each with an index, object type ('embedding'), and the embedding array (floats or base64-encoded), plus model name and token usage stats (prompt_tokens, total_tokens).
Example use cases
Semantic search index builder
“Take these 50 product descriptions and embed each one using text-embedding-3-small as float vectors so I can index them in my vector database for semantic search.”
RAG query vectorization
“I need to embed this user query as a float vector with text-embedding-3-small so I can run a nearest-neighbor search against my document store: 'What are the side effects of ibuprofen?'”
Sentence similarity scoring
“Generate text-embedding-3-small embeddings for these two sentences so I can compute their cosine similarity: 'The cat sat on the mat' and 'A feline rested on a rug.'”
Technical details
Endpoint
POSThttps://openai.mm.family/x402/v1/models/text-embedding-3-small/embeddings?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need cost-efficient, high-quality text embeddings via OpenAI's text-embedding-3-small model and want to pay per call in USDC without managing an OpenAI API key. Prefer over text-embedding-3-large when speed and cost matter more than maximum embedding quality, and prefer over ada-002 for better performance at similar cost. Ideal for agents operating in crypto-native or x402-compatible payment environments.
Side effects
- Input exceeds 8192 token limit — request rejected
- Insufficient USDC balance for x402 payment — 402 Payment Required response
- Invalid model value (must be 'text-embedding-3-small') — 400 validation error
- Malformed input array (unsupported types) — 422 unprocessable entity
- Rate limiting or upstream OpenAI outage — 503 or 429 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | — | |
| model | string | |
| dimensions | integer | |
| encoding_format | string |
Output
Schema · Response
{
"type": "json",
"example": {
"data": [
{
"index": 0,
"object": "embedding",
"embedding": [
0.01,
-0.02
]
}
],
"model": "text-embedding-3-small",
"usage": {
"total_tokens": 1,
"prompt_tokens": 1
},
"object": "list"
}
}Tags
x402
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