OpenAI Text Embeddings API

Overview

OpenAI’s text-embedding-3-large on RouterBase, served through the standard OpenAI-compatible embeddings endpoint. Returns dense vectors for semantic search, clustering, classification, and retrieval-augmented generation.


Provider	OpenAI
Family	`text-embedding-3-large`
Modality	Embedding
Max input	8191 tokens
Dimensions	up to 3072 (truncatable via `dimensions`)

Models

openai/text-embedding-3-large

Pricing is deliberately not reproduced here. Rates are set per model in the RouterBase catalogue and can be overridden per account, so any figure copied into this page is a snapshot that goes stale the next time a rate changes. Fetch the current rate for any model from the Models API:

GET /api/models/{model}/pricing

URL-encode the slash in the model id — e.g. openai%2Ftext-embedding-3-large.

Endpoint

POST https://routerbase.com/v1/embeddings

Drop-in compatible with the OpenAI client — point it at https://routerbase.com/v1.

Quickstart

curl https://routerbase.com/v1/embeddings \
  -H "Authorization: Bearer $ROUTERBASE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/text-embedding-3-large",
    "input": "The quick brown fox jumps over the lazy dog"
  }'

input accepts a single string or an array of strings to embed in one call. Optional parameters:

dimensions — truncate the output vector to a smaller size (e.g. 256).
encoding_format — "float" (default) or "base64".

Response

{
  "object": "list",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.0023, -0.0091, "..."] }
  ],
  "model": "openai/text-embedding-3-large",
  "usage": { "prompt_tokens": 11, "total_tokens": 11 }
}

Live catalogue + current rates: the Models API.

Get Started

API Reference

OpenAI Text Embeddings API

Overview

Models

Endpoint

Quickstart

Response

​Overview

​Models

​Endpoint

​Quickstart

​Response

Overview

Models

Endpoint

Quickstart

Response