text-embedding-ada-002 — price, context and performance

text-embedding-ada-002 is a OpenAI model available on AirAI. Input $0.10, output - per 1M tokens.

Overview

Embedding model for semantic search, retrieval, clustering, and ranking pipelines

Pricing

Only groups enabled for this model are listed.

Performance

FAQ

Model comparison

Troubleshooting

429 is a rate limit response. Lower your concurrency, retry with backoff, or switch to a plan with a larger quota.

Common causes

• Too many concurrent requests
• Quota of the current plan exhausted
• Retrying immediately without backoff

How to fix

• Limit concurrency and retry with exponential backoff
• Switch to a plan with a larger quota
• Cache repeated requests

How to connect

curl https://api.airai.cc/v1/chat/completions \
  -H "Authorization: Bearer <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-ada-002",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="<YOUR_API_KEY>",
    base_url="https://api.airai.cc/v1"
)

response = client.chat.completions.create(
    model="text-embedding-ada-002",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "<YOUR_API_KEY>",
  baseURL: "https://api.airai.cc/v1"
});

const response = await client.chat.completions.create({
  model: "text-embedding-ada-002",
  messages: [{ role: "user", content: "Hello" }]
});
console.log(response.choices[0].message.content);

const OpenAI = require("openai");

const client = new OpenAI({
  apiKey: "<YOUR_API_KEY>",
  baseURL: "https://api.airai.cc/v1"
});

client.chat.completions.create({
  model: "text-embedding-ada-002",
  messages: [{ role: "user", content: "Hello" }]
}).then((r) => console.log(r.choices[0].message.content));

Replace <YOUR_API_KEY> with the API Key from your token settings.

Compatible endpoints

Gemini SDK · TypeScript

import { GoogleGenerativeAI } from "@google/generative-ai";

const genAI = new GoogleGenerativeAI("<YOUR_API_KEY>");
const model = genAI.getGenerativeModel({ model: "text-embedding-ada-002" });

const result = await model.generateContent(
  "Explain quantum entanglement in one paragraph."
);
console.log(result.response.text());

Authentication

All requests must include the Authorization: Bearer <TOKEN> header. Anthropic-format endpoints also accept the x-api-key header. Generate your API Key on the Tokens page, where you can scope access by model, group, IP, and rate limits.

Supported parameters

Rate limits

Data updated: 2026-10-10 18:30