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GET
/
models
/
{modelId}
Get Model Details
curl --request GET \
  --url https://api.kakiyo.com/v1/models/{modelId} \
  --header 'Authorization: Bearer <token>'
{
  "id": "680321c8001e2f527d82",
  "name": "GPT 5 Mini",
  "pricing": {
    "input": 0.25,
    "output": 2,
    "cached": 0.1
  },
  "status": "active"
}

​
Overview

Get detailed information about a specific AI model by its ID. This endpoint returns comprehensive model information including pricing details and current status.

​
Path Parameters

​
modelId
string
required
The unique identifier of the model to retrieve

​
Use Cases

  • Model Verification: Confirm model availability before using in prompts
  • Pricing Lookup: Get current pricing for cost calculations
  • Integration Validation: Verify model details during system integration
  • Cost Analysis: Analyze specific model costs for budget planning

​
Response Structure

{
  "id": "680321c8001e2f527d82",
  "name": "GPT 5 Mini",
  "pricing": {
    "input": 0.25,
    "output": 2,
    "cached": 0.1
  },
  "status": "active"
}

​
Testing Example

curl -X GET "https://api.kakiyo.com/v1/models/680321c8001e2f527d82" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json"

// JavaScript/Node.js
const getModelDetails = async (modelId) => {
  const response = await fetch(`https://api.kakiyo.com/v1/models/${modelId}`, {
    method: 'GET',
    headers: {
      'Authorization': 'Bearer YOUR_API_KEY',
      'Content-Type': 'application/json'
    }
  });

  return await response.json();
};

// Usage example
const modelDetails = await getModelDetails('680321c8001e2f527d82');
console.log('Model Details:', modelDetails);

// Calculate cost for specific usage
const calculateUsageCost = (model, inputTokens, outputTokens) => {
  const inputCost = (inputTokens / 1000) * model.pricing.input;
  const outputCost = (outputTokens / 1000) * model.pricing.output;
  
  return {
    model: model.name,
    inputCost: inputCost.toFixed(4),
    outputCost: outputCost.toFixed(4),
    totalCost: (inputCost + outputCost).toFixed(4)
  };
};

const cost = calculateUsageCost(modelDetails, 10000, 5000);
console.log('Usage Cost:', cost);

# Python
import requests

def get_model_details(model_id):
    """Get detailed information about a specific model"""
    response = requests.get(
        f'https://api.kakiyo.com/v1/models/{model_id}',
        headers={
            'Authorization': 'Bearer YOUR_API_KEY',
            'Content-Type': 'application/json'
        }
    )
    
    return response.json()

# Usage example
model_details = get_model_details('680321c8001e2f527d82')
print('Model Details:', model_details)

# Cost calculation function
def calculate_cost(model, input_tokens, output_tokens):
    """Calculate cost for given token usage"""
    input_cost = (input_tokens / 1000) * model['pricing']['input']
    output_cost = (output_tokens / 1000) * model['pricing']['output']
    
    return {
        'model': model['name'],
        'input_cost': round(input_cost, 4),
        'output_cost': round(output_cost, 4),
        'total_cost': round(input_cost + output_cost, 4)
    }

# Calculate cost for 10K input, 5K output tokens
cost = calculate_cost(model_details, 10000, 5000)
print('Estimated Cost:', cost)

​
Error Responses

​
Model Not Found

{
  "error": "not_found",
  "message": "Model not found"
}

​
Authentication Failed

{
  "error": "unauthorized",
  "message": "Invalid or missing API key"
}

​
Internal Server Error

{
  "error": "internal_error",
  "message": "An internal error occurred while fetching model details"
}

​
Integration Examples

​
Model Validation

const validateModel = async (modelId) => {
  try {
    const model = await getModelDetails(modelId);
    
    if (model.status !== 'active') {
      throw new Error(`Model ${model.name} is not active`);
    }
    
    return {
      valid: true,
      model: model
    };
  } catch (error) {
    return {
      valid: false,
      error: error.message
    };
  }
};

// Usage
const validation = await validateModel('680321c8001e2f527d82');
if (validation.valid) {
  console.log('Model is valid:', validation.model.name);
} else {
  console.error('Model validation failed:', validation.error);
}

​
Cost Comparison

const compareModelCosts = async (modelIds, inputTokens, outputTokens) => {
  const comparisons = [];
  
  for (const modelId of modelIds) {
    try {
      const model = await getModelDetails(modelId);
      const cost = calculateUsageCost(model, inputTokens, outputTokens);
      comparisons.push(cost);
    } catch (error) {
      console.error(`Failed to get details for model ${modelId}:`, error);
    }
  }
  
  // Sort by total cost
  return comparisons.sort((a, b) => parseFloat(a.totalCost) - parseFloat(b.totalCost));
};

// Usage
const modelIds = ['680321c8001e2f527d82', '680321aa001300a6673d', '689f6adb001e16e22378'];
const costComparison = await compareModelCosts(modelIds, 10000, 5000);
console.log('Cost Comparison (cheapest first):', costComparison);

​
Prompt Configuration Helper

const getModelForPrompt = async (modelId) => {
  const model = await getModelDetails(modelId);
  
  return {
    id: model.id,
    name: model.name,
    isActive: model.status === 'active',
    costPer1KTokens: {
      input: model.pricing.input,
      output: model.pricing.output,
      cached: model.pricing.cached
    },
    recommendedFor: getRecommendation(model)
  };
};

const getRecommendation = (model) => {
  const totalCost = model.pricing.input + model.pricing.output;
  
  if (totalCost <= 3) return 'Budget-friendly tasks, high-volume operations';
  if (totalCost <= 15) return 'Standard tasks, balanced performance and cost';
  return 'Complex tasks requiring highest quality output';
};

// Usage
const promptModel = await getModelForPrompt('680321c8001e2f527d82');
console.log('Model for Prompt:', promptModel);

​
Best Practices

  1. Model Verification: Always verify model status before using in production
  2. Cost Monitoring: Use model details for accurate cost tracking and budgeting
  3. Error Handling: Implement proper error handling for model not found scenarios
  4. Caching: Cache model details to reduce API calls for frequently used models
  5. Validation: Validate model availability before creating prompts or campaigns

​
Common Integration Patterns

​
Pre-Campaign Validation

Verify all models used in campaign prompts are active and available before launching campaigns.

​
Dynamic Model Selection

Use model details to dynamically select the most appropriate model based on current pricing and requirements.

​
Cost Optimization

Compare model costs for different scenarios to optimize AI usage expenses.

​
Model Status

  • active: Model is available for use
  • inactive: Model is temporarily unavailable (not returned by list endpoint)
Only active models are returned by the API endpoints, ensuring you only work with available models.

Authorizations

​
Authorization
string
header
required

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

Path Parameters

​
modelId
string
required

Response

Model details retrieved successfully

​
id
string
Example:

"680321c8001e2f527d82"

​
name
string
Example:

"GPT 5 Mini"

​
pricing
object
​
status
enum<string>
Available options:
active,
inactive
Example:

"active"

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