Text Embedding 3 Large

Model Information

Display Name: Text Embedding 3 Large

API Model ID: openai/text-embedding-3-large

Category: Text To Embedding

Description: OpenAI's most powerful embedding model, delivering state-of-the-art performance for demanding applications. **Key Features:** - Highest quality embeddings from OpenAI - Adjustable dimensions (256, 512, 1024, 1536, 3072) - Superior performance on complex semantic tasks - Best choice for accuracy-critical applications **Use Cases:** - High-precision semantic search - Complex document clustering - Fine-grained similarity matching - Enterprise RAG systems - Multi-language applications **Performance:** - MTEB benchmark: Top-tier across all tasks - Excellent multilingual capabilities - Best for nuanced semantic understanding

Context Window: 8,191 tokens

How to Use This Model

To use Text Embedding 3 Large via the HInow.ai API, use the model ID: openai/text-embedding-3-large

API Request Example (Chat/Text)


POST https://api.hinow.ai/v1/chat/completions
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "model": "openai/text-embedding-3-large",
  "messages": [
    {"role": "user", "content": "Your message here"}
  ]
}
              

Pricing

  • input: $0.18

Available Parameters

  • dimensions: Output vector dimensions. Lower = faster & cheaper, higher = more accurate (Options: 256, 512, 1024, 1536, 3072)

Quick Reference

To use this model, set: "model": "openai/text-embedding-3-large"

Featured: No

Documentation: https://hinow.ai/models/openai/text-embedding-3-large

API Endpoint: https://api.hinow.ai/v1

Back to Models
Text Embedding 3 Large

Text Embedding 3 Large

openai/text-embedding-3-large

$0.180
input

About

OpenAI's most powerful embedding model, delivering state-of-the-art performance for demanding applications.

Key Features:

  • Highest quality embeddings from OpenAI
  • Adjustable dimensions (256, 512, 1024, 1536, 3072)
  • Superior performance on complex semantic tasks
  • Best choice for accuracy-critical applications

Use Cases:

  • High-precision semantic search
  • Complex document clustering
  • Fine-grained similarity matching
  • Enterprise RAG systems
  • Multi-language applications

Performance:

  • MTEB benchmark: Top-tier across all tasks
  • Excellent multilingual capabilities
  • Best for nuanced semantic understanding

Capabilities

Text To Embedding
Context8K tokens

Parameters

dimensions

Output vector dimensions. Lower = faster & cheaper, higher = more accurate

256512102415363072

Code Examples

curl -X POST https://api.hinow.ai/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $HINOW_API_KEY" \
  -d '{
    "model": "openai/text-embedding-3-large",
    "input": "Your input here",
    "parameters": {
      "dimensions": "256"
    }
  }'