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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.

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Вход, $/1M $0.02

Выход, $/1M —

Контекст 8 192

Принимает текст

Последняя проверка 04.11.2026 12:00:14 UTC

Источник страница провайдера

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API

API, совместимый с OpenAI: подходят официальные SDK OpenAI с этим адресом. YOUR_API_KEY замените на свой ключ от провайдера.

Адрес API
https://go.fastrouter.ai/api/v1
Эндпоинт
https://go.fastrouter.ai/api/v1/embeddings
Модель (id в API)
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());
Запрос (JSON)
{
  "model": "openai/text-embedding-3-small",
  "input": [
    "first text",
    "second text"
  ]
}
Ответ (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
  }
}

Адрес взят из списка моделей провайдера - сверьте с его документацией.

Документация API провайдера

Source: AI Rate Card, https://airatecard.com/ru/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

Технические данные

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