Text embeddings on Venice models for retrieval, RAG, and semantic search, paid per request
Text embeddings on Venice models for retrieval, RAG, and semantic search, paid per request in USDC on Base via x402, no API key. Resolve a model id from GET /api/v1/models?type=embedding.
10000 (raw units)
price
8
calls / 30d
4
unique payers
2026-09-09
updated
Provider
x402.aispace.bot · discovered, not yet claimed by its owner
Payment (x402 accepts[])
[
{
"scheme": "exact",
"network": "eip155:8453",
"payTo": "0xA7f3Ad0E69F61864092FAbBa6Cee00AF6e584689",
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"amount": "10000",
"maxTimeoutSeconds": 300
},
{
"scheme": "exact",
"network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
"payTo": "5hqrYCkTNe5z9Uc8o29KDNd2Gn9YreE6ZthZ7QY5hrKY",
"asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
"amount": "10000",
"maxTimeoutSeconds": 300
}
]Output schema
{
"bazaar": {
"info": {
"input": {
"body": {
"input": "The quick brown fox jumps over the lazy dog.",
"model": "text-embedding-bge-m3"
},
"bodyType": "json",
"method": "POST",
"type": "http"
},
"output": {
"example": {
"data": [
{
"embedding": [
-0.05365830659866333
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-bge-m3",
"object": "list",
"usage": {
"prompt_tokens": 3,
"total_tokens": 3
}
},
"type": "json"
}
},
"related": [
"/models"
],
"schema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"properties": {
"input": {
"description": "String or array of strings to embed."
},
"model": {
"description": "Venice embedding model id. See GET /api/v1/models?type=embedding (e.g. text-embedding-bge-m3, gemini-embedding-2-preview).",
"type": "string"
}
},
"required": [
"model",
"input"
],
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST",
"PUT",
"PATCH"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"properties": {
"data": {
"items": {
"properties": {
"embedding": {
"items": {
"type": "number"
},
"type": "array"
},
"index": {
"type": "number"
},
"object": {
"type": "string"
}
},
"type": "object"
},
"type": "array"
},
"model": {
"type": "string"
},
"object": {
"type": "string"
},
"usage": {
"properties": {
"prompt_tokens": {
"type": "number"
},
"total_tokens": {
"type": "number"
}
},
"type": "object"
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}
},
"chainId": 8453,
"estimateBasis": "embeddings_tokens_11",
"priceMult": 0.5,
"tokenDecimals": 6,
"upstreamUsd": 0.0000016499999999999999
}Use it
curl
curl "https://x402.aispace.bot/api/v1/embeddings" # -> 402 Payment Required, accepts[] lists how to pay # retry with a PAYMENT-SIGNATURE (or PAYMENT header) once paid
JavaScript
const res = await fetch("https://x402.aispace.bot/api/v1/embeddings");
if (res.status === 402) {
const { accepts } = await res.json();
// pay one of accepts[] via an x402 client, then retry with the payment header
}Python
import httpx
res = httpx.get("https://x402.aispace.bot/api/v1/embeddings")
if res.status_code == 402:
accepts = res.json()["accepts"]
# pay one of accepts[] via an x402 client, then retry with the payment headerMachine-readable
Everything on this page is also available as clean JSON at /resources/778.json, and this resource appears in /discovery/resources and /discovery/search.