Getting Started
Model Selection Guide

Model Selection Guide

Choosing the right model for your needs is essential for optimal performance and cost-efficiency. This guide will help you understand the different models available in Your App and how to select the most appropriate one for your use case.

Available Models

Selection Factors

When choosing a model, consider these key factors:

Task Complexity

  • Simple tasks (classification, basic Q&A): Standard or Fast models
  • Medium complexity (content generation, summarization): Advanced model
  • Complex tasks (research, analysis, specialized domains): Expert model

Response Time Requirements

  • Real-time applications: Fast model
  • Interactive but not time-critical: Standard model
  • Batch processing or background tasks: Advanced or Expert models

Token Limits

Different models have different context window sizes (the amount of text they can process at once).

  • Standard: 4,000 tokens
  • Advanced: 8,000 tokens
  • Expert: 16,000 tokens
  • Fast: 2,000 tokens
  • Efficient: 4,000 tokens

Cost Considerations

Models are priced per 1,000 tokens processed (input + output):

ModelPrice per 1K tokens
Standard$0.005
Advanced$0.015
Expert$0.030
Fast$0.004
Efficient$0.003

Domain Specificity

If your task involves specialized knowledge (legal, medical, scientific, etc.), consider:

  1. Using the Expert model, which has broader knowledge across domains
  2. Fine-tuning a Custom model on your domain-specific data
  3. Using specialized models if available for your domain

Recommended Configurations

Here are some common use cases and the recommended model configurations:

Content Creation

  • Blog posts: Advanced model with temperature 0.7
  • Technical documentation: Expert model with temperature 0.2
  • Creative writing: Advanced model with temperature 0.9

Conversational AI

  • Customer support: Standard model with temperature 0.5
  • Virtual assistants: Advanced model with temperature 0.6
  • Educational chatbots: Expert model with temperature 0.4

Data Analysis

  • Basic data summarization: Standard model with temperature 0.3
  • Complex pattern recognition: Expert model with temperature 0.2
  • Report generation: Advanced model with temperature 0.4

Testing Your Model Selection

It's recommended to test different models for your specific use case before committing to a particular configuration. You can use our Model Comparison Tool to evaluate performance across different models and parameters.

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Start with the simplest (and most cost-effective) model that might meet your needs, and only upgrade if necessary. This approach will help optimize your costs while ensuring adequate performance.