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text-embedding-3-small - In-Depth Overview

OpenAI · OpenAI

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Latest in family

Model ID: text-embedding-3-small

Get all the details on text-embedding-3-small, an AI model from OpenAI. This page covers its token limits, pricing structure, key capabilities such as text_embedding, semantic_search, Clustering, available API code samples, and performance strengths.

Key Metrics

Input Limit

No data tokens

Output Limit

No data tokens

Input Cost

$0.02/1M

Output Cost

$0.02/1M

Sample API Code

from openai import OpenAI
client = OpenAI()
response = client.embeddings.create(
    input="The quick brown fox jumps over the lazy dog",
    model="text-embedding-3-small"
)
embedding = response.data[0].embedding

Required Libraries

openai
openai

Notes

text-embedding-3-small is an improved, more performant version of OpenAI's ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text.

Supported Data Types

Input Types

text

Output Types

vector

Strengths & Weaknesses

Exceptional at

text embedding
relatedness measurement

Good at

search
clustering
recommendations
anomaly detection
classification

Additional Information

Latest Update

Jan 25, 2024

Knowledge Cutoff

No data