Choosing the Right Model

Match model capabilities to task requirements.

The 90/10 Rule

90% of tasks work well with smaller, cheaper models.

Task-Based Selection

const modelMap = {
  // Simple tasks → cheap models
  classification: 'gpt-3.5-turbo',
  extraction: 'gpt-3.5-turbo',
  summarization: 'gpt-3.5-turbo',
  
  // Complex tasks → capable models
  complex_reasoning: 'gpt-4',
  code_generation: 'gpt-4',
  creative_writing: 'gpt-4',
};

function getModel(task: keyof typeof modelMap) {
  return modelMap[task] || 'gpt-3.5-turbo';
}

Cost Comparison

GPT-4 is 60x more expensive than GPT-3.5 for input tokens!

Decision Framework

• Start with the cheapest model
• Measure quality on your specific task
• Only upgrade if quality is insufficient
• Consider fine-tuning small models for repeated tasks