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Overview

The models endpoint returns a list of available AI models accessible through your Codex-LB instance. Each model includes metadata about capabilities, reasoning support, and configuration options.

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Endpoint

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GET /backend-api/codex/models

Retrieves the list of available models. Base URL: https://your-codex-lb-instance.com

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Query Parameters

None.

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Response

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object
string
Always returns "list"
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data
array
Array of model objects

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Example Response

{
  "object": "list",
  "data": [
    {
      "id": "gpt-5.1",
      "object": "model",
      "created": 1704067200,
      "owned_by": "codex-lb",
      "metadata": {
        "display_name": "GPT-5.1",
        "description": "Advanced reasoning model with extended context",
        "context_window": 128000,
        "input_modalities": ["text", "image"],
        "supported_reasoning_levels": [
          {
            "effort": "low",
            "description": "Fast responses with minimal reasoning"
          },
          {
            "effort": "medium",
            "description": "Balanced reasoning and speed"
          },
          {
            "effort": "high",
            "description": "Maximum reasoning depth and accuracy"
          }
        ],
        "default_reasoning_level": "medium",
        "supports_reasoning_summaries": true,
        "support_verbosity": true,
        "default_verbosity": "standard",
        "prefer_websockets": false,
        "supports_parallel_tool_calls": true,
        "supported_in_api": true,
        "minimal_client_version": null,
        "priority": 100
      }
    },
    {
      "id": "gpt-4o",
      "object": "model",
      "created": 1704067200,
      "owned_by": "codex-lb",
      "metadata": {
        "display_name": "GPT-4o",
        "description": "Fast and efficient multimodal model",
        "context_window": 128000,
        "input_modalities": ["text", "image", "audio"],
        "supported_reasoning_levels": [],
        "default_reasoning_level": null,
        "supports_reasoning_summaries": false,
        "support_verbosity": false,
        "default_verbosity": null,
        "prefer_websockets": false,
        "supports_parallel_tool_calls": true,
        "supported_in_api": true,
        "minimal_client_version": null,
        "priority": 90
      }
    }
  ]
}

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Example Request

curl -X GET https://your-codex-lb-instance.com/backend-api/codex/models \
  -H "Authorization: Bearer YOUR_API_KEY"

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Authentication

This endpoint requires authentication using an API key. Include your API key in the Authorization header: 
Authorization: Bearer YOUR_API_KEY

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API Key Model Filtering

If your API key has restricted access to specific models (configured via the allowed_models field), the response will only include models that your key is authorized to use.

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Rate Limiting

This endpoint counts against your API key’s rate limit, even though it doesn’t make requests to upstream AI providers. This is to enforce fair usage of the Codex-LB infrastructure.

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Use Cases

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Selecting Models by Capability

import requests

def get_models_with_reasoning(api_key):
    response = requests.get(
        "https://your-codex-lb-instance.com/backend-api/codex/models",
        headers={"Authorization": f"Bearer {api_key}"}
    )
    models = response.json()["data"]
    
    return [
        model["id"] 
        for model in models 
        if model["metadata"]["supported_reasoning_levels"]
    ]

reasoning_models = get_models_with_reasoning("your-api-key")
print(f"Models with reasoning: {reasoning_models}")

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Finding Models by Context Window

def get_models_by_context(api_key, min_context=100000):
    response = requests.get(
        "https://your-codex-lb-instance.com/backend-api/codex/models",
        headers={"Authorization": f"Bearer {api_key}"}
    )
    models = response.json()["data"]
    
    return [
        {
            "id": model["id"],
            "name": model["metadata"]["display_name"],
            "context": model["metadata"]["context_window"]
        }
        for model in models
        if model["metadata"]["context_window"] >= min_context
    ]

large_context_models = get_models_by_context("your-api-key", min_context=128000)
for model in large_context_models:
    print(f"{model['name']}: {model['context']:,} tokens")

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Notes

  • Model availability depends on the accounts configured in your Codex-LB instance
  • The priority field affects load balancing decisions when multiple models are suitable
  • Models with supported_in_api: false are not available via API endpoints
  • The prefer_websockets flag indicates the recommended connection type for optimal performance
  • Model metadata is cached and refreshed periodically based on your configuration

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