Text Embedding 3 Large overview
Text Embedding 3 Large by OpenAI
Text-embedding-3-large API provides top-tier text embeddings with customizable dimensions, delivering exceptional accuracy for complex applications.
Text Embedding 3 Large specs
- Model ID
openai/text-embedding-3-large- Developer
- OpenAI
- Input
- Text
- Output
- Text
- Endpoint
POST https://api.aimlapi.com/v1/embeddings
Basic Information
- Model Name: text-embedding-3-large
- Release Date: January 25th, 2024
- Version: text-embedding-3-large
- Overview:text-embedding-3-large is a next-generation embedding model that offers superior performance and flexibility. It converts text into high-dimensional numerical representations that are highly effective for various machine learning tasks.
- Key Features:
- Top Performance: The highest performing embedding model with significant improvements over predecessors.
- Flexible Embedding Size: Supports dimensions from 256 up to 3072, allowing for trade-offs between performance and resource usage.
- Native Support for Shortening Embeddings: Developers can shorten embeddings without significant loss in conceptual representation.
- Intended Use:
- High-Performance Search: Optimal for applications requiring precise and fast search results.
- Advanced Clustering: Suitable for sophisticated data analysis and clustering tasks.
- Enhanced Recommendations: Provides accurate recommendations by understanding text similarities.
- Robust Anomaly Detection: Efficiently identifies outliers in large datasets.
- Detailed Diversity Measurement: Analyzes the diversity of large text corpora.
- Accurate Classification: Highly effective in classifying complex text data.
- Language Support:Offers improved support for multiple languages, making it suitable for global applications.
Technical Details
- Architecture:Advanced transformer-based architecture designed for high-dimensional embeddings and superior performance.
- Training Data:Trained on an extensive and diverse dataset to capture a wide array of linguistic nuances.
- Data Source and Size:Includes billions of text entries, ensuring a comprehensive understanding of language.
- Diversity and Bias:Ensures high diversity in training data to mitigate biases and enhance reliability.
Performance Metrics
- Comparison to Other Models:
- MIRACL Score: Increased from 31.4% (ada-002) to 54.9%.
- MTEB Score: Improved from 61.0% (ada-002) to 64.6%.
- Accuracy:Delivers top-tier accuracy across multiple benchmarks.
- Speed:Optimized for faster processing times despite larger dimensionality.
- Robustness:Maintains high performance across a variety of input types and contexts.
Use cases
Build enterprise-grade search engines: queries map to documents or products using rich embeddings for high relevance across languages.
Multilingual recommendation systems
Use embeddings to cluster and match content/users in diverse languages, ideal for global apps (e‑commerce, media, etc.).
Combine embeddings with vector databases for retrieval-augmented agents that need deep semantic understanding.
Text Embedding 3 Large API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.13 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
How to use the Text Embedding 3 Large API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/embeddings' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "openai/text-embedding-3-large",
"input": "The quick brown fox jumps over the lazy dog."
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "openai/text-embedding-3-large",
"input": "The quick brown fox jumps over the lazy dog."
}
response = requests.post("https://api.aimlapi.com/v1/embeddings", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/embeddings", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "openai/text-embedding-3-large",
"input": "The quick brown fox jumps over the lazy dog."
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Text Embedding 3 Large
Text Embedding 3 Large FAQ
What inputs and outputs does Text Embedding 3 Large support?
Text Embedding 3 Large takes text as input and returns embedding.
When was Text Embedding 3 Large released?
Text Embedding 3 Large became available on December 12, 2025.
How much does Text Embedding 3 Large cost?
Text Embedding 3 Large costs $0.13 per 1M input tokens on AI/ML API, billed as you go with no subscription.
Who created Text Embedding 3 Large?
Text Embedding 3 Large was built by OpenAI.
How do I call Text Embedding 3 Large on AI/ML API?
Send a request to https://api.aimlapi.com/v1/embeddings with openai/text-embedding-3-large as the model id.
Is Text Embedding 3 Large available through a single API key?
Yes. Text Embedding 3 Large is served through AI/ML API, so the same key and endpoint format used for other models applies.
What type of model is this?
It is an embeddings model that converts text into vector representations.
What is the Text Embedding 3 Large model ID?
Use openai/text-embedding-3-large as the model parameter. Requests go to https://api.aimlapi.com/v1/embeddings with your AI/ML API key.