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Text Embedding 3 Small

Model Information

Display Name: Text Embedding 3 Small

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

Category: Text To Embedding

Description: OpenAI's newest and most efficient embedding model, optimized for cost-effectiveness while maintaining strong performance. **Key Features:** - Best price-performance ratio for embeddings - Adjustable dimensions (256, 512, 1536) - 5x cheaper than ada-002 with better performance - Ideal for large-scale applications **Use Cases:** - Semantic search - Clustering and classification - Recommendations - RAG (Retrieval Augmented Generation) - Anomaly detection **Performance:** - MTEB benchmark: Strong performance across tasks - Optimized for English, good multilingual support - Lower latency than large variant

Context Window: 8,191 tokens

How to Use This Model

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

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-small",
  "messages": [
    {"role": "user", "content": "Your message here"}
  ]
}

Pricing

  • input: $0.03

Available Parameters

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

Quick Reference

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

Featured: No

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

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

Back to Models
Text Embedding 3 Small

Text Embedding 3 Small

openai/text-embedding-3-small

$0.030
input

About

OpenAI's newest and most efficient embedding model, optimized for cost-effectiveness while maintaining strong performance.

Key Features:

  • Best price-performance ratio for embeddings
  • Adjustable dimensions (256, 512, 1536)
  • 5x cheaper than ada-002 with better performance
  • Ideal for large-scale applications

Use Cases:

  • Semantic search
  • Clustering and classification
  • Recommendations
  • RAG (Retrieval Augmented Generation)
  • Anomaly detection

Performance:

  • MTEB benchmark: Strong performance across tasks
  • Optimized for English, good multilingual support
  • Lower latency than large variant

Capabilities

Text To Embedding
Context8K tokens

Parameters

dimensions

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

2565121536

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-small",
    "input": "Your input here",
    "parameters": {
      "dimensions": "256"
    }
  }'