Embedding V1 · aihubmix

Embedding-V1 is a text representation model based on Baidu's Wenxin large model technology, capable of converting text into numerical vector forms for applications such as text retrieval, information recommendation, and knowledge mining. Embedding-V1 provides an Embeddings interface that generates corresponding vector representations based on the input content. By calling this interface, you can input text into the model and obtain the corresponding vector representations for subsequent text processing and analysis.

Base model All models on this base All models of the provider to the provider

Input, $/1M $0.068

Output, $/1M —

Context —

Accepts text

Last checked 04.11.2026 12:00:14 UTC

Source provider's page

Price alerts

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://aihubmix.com/api/v1`
Endpoint	`https://aihubmix.com/api/v1/embeddings`
Model id	`embedding-v1`

curl

curl https://aihubmix.com/api/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "embedding-v1", "input": ["first text", "second text"]}'

Python

import requests

r = requests.post(
    "https://aihubmix.com/api/v1/embeddings",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
      "model": "embedding-v1",
      "input": [
        "first text",
        "second text"
      ]
    },
)
print(r.json())

JavaScript

const r = await fetch("https://aihubmix.com/api/v1/embeddings", {
  method: "POST",
  headers: {Authorization: "Bearer YOUR_API_KEY", "Content-Type": "application/json"},
  body: JSON.stringify({
    "model": "embedding-v1",
    "input": [
      "first text",
      "second text"
    ]
  }),
});
console.log(await r.json());

Request (JSON)

{
  "model": "embedding-v1",
  "input": [
    "first text",
    "second text"
  ]
}

Response (JSON)

{
  "object": "list",
  "model": "embedding-v1",
  "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%3Aaihubmix%7Cembedding-v1, prices checked 2026-11-04; seller's page: https://aihubmix.com

Technical details

ID: offer:aihubmix|embedding-v1