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OpenAI: text-embedding-3-small · fastrouter

text-embedding-3-small is a compact OpenAI text embedding model designed for general-purpose semantic tasks (search, classification, similarity) with high throughput. It produces 1536-dimensional vectors and is optimized for efficiency. Its cost is very low (about $0.02 per 1K tokens), making it far cheaper than larger models, though its accuracy is correspondingly slightly lower (MTEB benchmark ~62.3%). The model is ideal for cost-sensitive or high-throughput scenarios where good semantic embeddings are needed but ultra-high accuracy is not critical. In practice, it still performs well on search and retrieval tasks, but trades off some accuracy and richness of representation relative to the larger embedding models.

Base modelAll models on this baseAll models of the providerto the provider

Input, $/1M $0.02

Output, $/1M —

Context 8 192

Accepts text

Last checked 04.11.2026 12:00:14 UTC

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API

OpenAI-compatible API: the official OpenAI SDKs work with this base URL. Replace YOUR_API_KEY with your key from the provider.

API base URL
https://go.fastrouter.ai/api/v1
Endpoint
https://go.fastrouter.ai/api/v1/embeddings
Model id
openai/text-embedding-3-small
curl
curl https://go.fastrouter.ai/api/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "openai/text-embedding-3-small", "input": ["first text", "second text"]}'
Python
import requests

r = requests.post(
    "https://go.fastrouter.ai/api/v1/embeddings",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
      "model": "openai/text-embedding-3-small",
      "input": [
        "first text",
        "second text"
      ]
    },
)
print(r.json())
JavaScript
const r = await fetch("https://go.fastrouter.ai/api/v1/embeddings", {
  method: "POST",
  headers: {Authorization: "Bearer YOUR_API_KEY", "Content-Type": "application/json"},
  body: JSON.stringify({
    "model": "openai/text-embedding-3-small",
    "input": [
      "first text",
      "second text"
    ]
  }),
});
console.log(await r.json());
Request (JSON)
{
  "model": "openai/text-embedding-3-small",
  "input": [
    "first text",
    "second text"
  ]
}
Response (JSON)
{
  "object": "list",
  "model": "openai/text-embedding-3-small",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0.0123,
        -0.0456,
        "..."
      ]
    }
  ],
  "usage": {
    "prompt_tokens": 6,
    "total_tokens": 6
  }
}

The address is taken from the provider's model list; check it against the provider's documentation.

Provider's API documentation

Source: AI Rate Card, https://airatecard.com/en/c/offer%3Afastrouter%7Copenai/text-embedding-3-small, prices checked 2026-11-04; seller's page: https://fastrouter.ai/models/openai/text-embedding-3-small

Technical details

ID: offer:fastrouter|openai/text-embedding-3-small