OpenAI: Text Embedding 3 Small
1 provider live- 1 live provider
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
- Context
- 8K
- tokens
- Dimensions
- 1,536
- per vector
- Input
- $0.02
- per million tokens
Providers
Ranked by price and speed. Requests go to the best healthy provider, then fail over down the list.| # | Provider | Input |
|---|---|---|
| 1 | Data policy not declared | $0.02 |
Price history
No price changes since Oct 25, 2026.
- OpenAI$0.02 in
Questions
How much does OpenAI: Text Embedding 3 Small cost?
OpenAI: Text Embedding 3 Small costs $0.02 per million input tokens at OpenAI, the provider requests go to first.
Do providers train on my prompts?
Each provider declares it, and the table above shows every declaration. You can limit a request to providers that keep nothing, or to providers in the EU.
Similar models
Call it
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.llm.buzz/api/v1",
api_key=os.environ["LLM_BUZZ_KEY"],
)
result = client.embeddings.create(
model="openai/text-embedding-3-small",
input="Hello",
)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.llm.buzz/api/v1",
apiKey: process.env.LLM_BUZZ_KEY,
});
const result = await client.embeddings.create({
model: "openai/text-embedding-3-small",
input: "Hello",
});curl https://api.llm.buzz/api/v1/embeddings \
-H "Authorization: Bearer $LLM_BUZZ_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "openai/text-embedding-3-small", "input": "Hello"}'Endpoints
POST /api/v1/embeddingsAuthentication
Send your llm.buzz key as a Bearer token: Authorization: Bearer $LLM_BUZZ_KEY. Create keys in the console. The same key calls every model; each request pays the price of the provider that answered it.
More in Authentication and the API reference.
README
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
- Model ID
- openai/text-embedding-3-small
- Takes
- Text
- Answers
- Embeddings
- Context
- 8K tokens
- Dimensions
- 1,536
- Weights
- Closed
- On llm.buzz since
- Oct 25, 2026