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GET
/
v1
/
embedding-models
cURL
curl --request GET \
  --url https://nano-gpt.com/api/v1/embedding-models \
  --header 'Authorization: Bearer <token>'
{
  "object": "list",
  "data": [
    {
      "id": "text-embedding-3-small",
      "object": "model",
      "created": 1754480583,
      "owned_by": "openai",
      "name": "Text Embedding 3 Small",
      "description": "Most cost-effective OpenAI embedding model with dimension reduction support",
      "dimensions": 1536,
      "supports_dimensions": true,
      "max_tokens": 8191,
      "pricing": {
        "per_million_tokens": 0.02,
        "currency": "USD"
      }
    }
  ]
}

​
Overview

The /api/v1/embedding-models endpoint provides a comprehensive list of available embedding models with detailed information including dimensions, pricing, and features. This endpoint returns all embedding models in OpenAI-compatible format.

​
Authentication

Authentication is optional but may enable user-specific features:
HeaderFormatRequiredDescription
AuthorizationBearer {api_key}OptionalAPI key for authenticated access
x-api-key{api_key}OptionalAlternative API key header

​
Response Format

Returns a list of all available embedding models with comprehensive details: 
{
  "object": "list",
  "data": [
    {
      "id": "text-embedding-3-small",
      "object": "model",
      "created": 1754480583,
      "owned_by": "openai",
      "name": "Text Embedding 3 Small",
      "description": "Most cost-effective OpenAI embedding model with dimension reduction support",
      "dimensions": 1536,
      "supports_dimensions": true,
      "max_tokens": 8191,
      "pricing": {
        "per_million_tokens": 0.02,
        "currency": "USD"
      }
    },
    {
      "id": "text-embedding-3-large",
      "object": "model",
      "created": 1754480583,
      "owned_by": "openai",
      "name": "Text Embedding 3 Large",
      "description": "Highest performance OpenAI embedding model with dimension reduction support",
      "dimensions": 3072,
      "supports_dimensions": true,
      "max_tokens": 8191,
      "pricing": {
        "per_million_tokens": 0.13,
        "currency": "USD"
      }
    },
    {
      "id": "BAAI/bge-m3",
      "object": "model",
      "created": 1754480583,
      "owned_by": "baai",
      "name": "BGE M3",
      "description": "Multilingual embedding model with excellent performance across languages",
      "dimensions": 1024,
      "supports_dimensions": false,
      "max_tokens": 8192,
      "pricing": {
        "per_million_tokens": 0.01,
        "currency": "USD"
      }
    }
    // ... more models
  ]
}

​
Field Descriptions

FieldTypeDescription
idstringUnique model identifier to use in embedding requests
objectstringAlways “model” for OpenAI compatibility
creatednumberUnix timestamp of response creation
owned_bystringModel provider (openai, baai, jina, etc.)
namestringHuman-readable model name
descriptionstringDetailed model description and use cases
dimensionsnumberDefault embedding vector dimensions
supports_dimensionsbooleanWhether model supports dimension reduction
max_tokensnumberMaximum input tokens supported
pricingobjectPricing information object

​
Pricing Object Structure

FieldTypeDescription
per_million_tokensnumberCost per million tokens in USD
currencystringAlways “USD”

​
Model Categories

​
OpenAI Models

High-quality embeddings with dimension reduction support:
  • text-embedding-3-small - Balance of cost and performance
  • text-embedding-3-large - Maximum accuracy
  • text-embedding-ada-002 - Legacy model

​
Multilingual Models

Support for multiple languages:
  • BAAI/bge-m3 - Excellent multilingual support
  • jina-clip-v1 - Multimodal CLIP embeddings

​
Language-Specific Models

Optimized for specific languages:
  • English: BAAI/bge-large-en-v1.5, jina-embeddings-v2-base-en
  • Chinese: BAAI/bge-large-zh-v1.5, jina-embeddings-v2-base-zh, zhipu-embedding-2
  • German: jina-embeddings-v2-base-de
  • Spanish: jina-embeddings-v2-base-es

​
Specialized Models

Domain-specific embeddings:
  • jina-embeddings-v2-base-code - Optimized for code
  • Baichuan-Text-Embedding - General purpose
  • Qwen/Qwen3-Embedding-0.6B - Efficient with dimension reduction

​
Usage Examples

​
Basic Request

curl "https://nano-gpt.com/api/v1/embedding-models"

​
With Authentication

curl "https://nano-gpt.com/api/v1/embedding-models" \
  -H "Authorization: Bearer your_api_key_here"

​
Python Example

import requests

# Discover available embedding models
response = requests.get("https://nano-gpt.com/api/v1/embedding-models")
models = response.json()

# Display models sorted by price
for model in sorted(models["data"], key=lambda x: x["pricing"]["per_million_tokens"]):
    print(f"{model['id']}: ${model['pricing']['per_million_tokens']}/1M tokens - {model['dimensions']} dims")

​
JavaScript Example

// Discover available embedding models
const response = await fetch("https://nano-gpt.com/api/v1/embedding-models");
const models = await response.json();

// Find models that support dimension reduction
const flexibleModels = models.data.filter(m => m.supports_dimensions);
console.log("Models with dimension reduction:", flexibleModels.map(m => m.id));

​
Model Selection Guide

Use CaseRecommended ModelsRationale
General English texttext-embedding-3-smallBest price/performance ratio
Maximum accuracytext-embedding-3-largeHighest quality embeddings
Multilingual contentBAAI/bge-m3Excellent cross-language performance
Code embeddingsjina-embeddings-v2-base-codeSpecialized for programming languages
Budget-consciousBAAI/bge-large-en-v1.5$0.01/1M tokens
Chinese contentBAAI/bge-large-zh-v1.5Optimized for Chinese
Fast similarity searchModels with supports_dimensions: trueCan reduce dimensions for speed

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Response

List of available embedding models

​
object
string
required

Always 'list'

Example:

"list"

​
data
object[]
required

Array of embedding model objects