POST /v1/embeddings

OpenAI-compatible endpoint to generate text embeddings — dense vectors of a text for retrieval, clustering, classification or RAG. Billed per input token.

Available models

Model	Dimensions	Price /1M tokens
`openai/text-embedding-3-small`	1536	$0.02 USD
`openai/text-embedding-3-large`	3072	$0.13 USD

Basic example

curl -X POST https://api.geekhub.mx/v1/embeddings \
  -H "Authorization: Bearer ghub_sk_live_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/text-embedding-3-small",
    "input": "The quick brown fox jumps over the lazy dog"
  }'

Response:

{
  "object": "list",
  "model": "openai/text-embedding-3-small",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.012, -0.043, ...] }
  ],
  "usage": {
    "prompt_tokens": 12,
    "total_tokens": 12,
    "cost_usd": 0.00000025,
    "cost_mxn": 0.000005
  }
}

Batching

input also accepts an array (up to 2048 items):

{
  "model": "openai/text-embedding-3-large",
  "input": [
    "First document…",
    "Second document…",
    "Third…"
  ]
}

data in the response is ordered to match the input.

Reduce dimensions

-3-* models let you request a lower dimensionality (useful to shrink storage in your vector DB):

{
  "model": "openai/text-embedding-3-large",
  "input": "Text…",
  "dimensions": 512
}

Note: price is per input token, not per dimension. Reducing dimensions doesn’t reduce the embedding cost — only your storage cost and search latency.

Zero Data Retention

Same rules as /chat/completions — set zdr: true or configure your guardrail. OpenAI’s text-embedding-3-* is on the verified list.

Managed vector store

Coming: POST /v1/vector-stores for hosted collections, upload and semantic query without running your own Pinecone/pgvector. For now, use the endpoint directly and store vectors wherever your infrastructure lives.

Get started

Concepts

Advanced features

Legal & compliance

API Reference

Models

POST /v1/embeddings

Available models

Basic example

Batching

Reduce dimensions

Zero Data Retention

Managed vector store

​Available models

​Basic example

​Batching

​Reduce dimensions

​Zero Data Retention

​Managed vector store

Available models

Basic example

Batching

Reduce dimensions

Zero Data Retention

Managed vector store