# OpenAI text-embedding-3-large (via mm.family x402)

> OpenAI text-embedding-3-large (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 high-dimensional vector embeddings for text using OpenAI's text-embedding-3-large model, billed per call in USDC via x402 micropayments.

## Facts

- Endpoint: POST https://openai.mm.family/x402/v1/models/text-embedding-3-large/embeddings?utm_source=zero.xyz
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/openai-text-embedding-3-large-via-mm-family-x402-e2487aea
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_y_0sLSinZ_TSmBOF9ltZd

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability openai-text-embedding-3-large-via-mm-family-x402-e2487aea -d '<json body>'
```

Example prompt: Embed this sentence using text-embedding-3-large and return the float vector: 'The quick brown fox jumps over the lazy dog'.

## When to prefer this

Choose this endpoint when you need high-quality, large-dimensional text embeddings from OpenAI's best embedding model and want to pay per call in USDC without a subscription. Prefer it over text-embedding-3-small when embedding quality and recall matter more than cost. Ideal for RAG pipelines, semantic search, document clustering, and similarity tasks requiring OpenAI's state-of-the-art embedding model with x402 micropayment support.

## Known failure modes

- Input exceeds 8192 token limit — request rejected
- Insufficient USDC balance for x402 payment — 402 Payment Required
- Invalid model field value (must be 'text-embedding-3-large') — 400 Bad Request
- Malformed input type (not string or array) — 400 validation error
- Invalid encoding_format value — 400 Bad Request
- Network timeout or provider outage — 5xx error

## How this service works

text-embedding-3-large: OpenAI Text Embedding 3 Large embeddings, paid per call in USDC. OpenAI list $0.13 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 an array of embedding objects, each with an index, object type 'embedding', and the embedding as a float (or base64-encoded) array. Also includes the model name used and token usage counts (prompt_tokens, total_tokens).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "input": {
   "type": [
    "string",
    "array"
   ]
  },
  "model": {
   "enum": [
    "text-embedding-3-large"
   ],
   "type": "string"
  },
  "dimensions": {
   "type": "integer"
  },
  "encoding_format": {
   "enum": [
    "float",
    "base64"
   ],
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "data": [
   {
    "index": 0,
    "object": "embedding",
    "embedding": [
     0.01,
     -0.02
    ]
   }
  ],
  "model": "text-embedding-3-large",
  "usage": {
   "total_tokens": 1,
   "prompt_tokens": 1
  },
  "object": "list"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/openai-text-embedding-3-large-via-mm-family-x402-e2487aea/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from openai.mm.family](https://www.zero.xyz/host/openai.mm.family/llms.txt)