Understanding Model Capabilities
Modern AI models each have distinct strengths and characteristics. Understanding these differences is essential for optimal model selection.
GPT-4 & GPT-4 Turbo
OpenAI's flagship models excel at general-purpose tasks with strong reasoning capabilities. Best for: creative content, complex instructions, broad knowledge tasks.
Claude 3 (Opus, Sonnet, Haiku)
Anthropic's models are known for nuanced understanding and safety. Best for: long documents, analytical tasks, situations requiring careful judgment.
Gemini Pro & Ultra
Google's models offer strong multimodal capabilities and integration with Google services. Best for: image understanding, data analysis, Google Workspace integration.
Model Comparison Matrix
Speed vs. Quality Tradeoffs
- Fastest: GPT-3.5 Turbo, Gemini Flash, Claude Haiku
- Balanced: GPT-4 Turbo, Claude Sonnet, Gemini Pro
- Highest Quality: GPT-4, Claude Opus, Gemini Ultra
Use Case Recommendations
Customer Support
Start with fast models (Haiku, GPT-3.5) for simple queries, escalate to powerful models for complex issues.
Document Analysis
Claude models handle long contexts exceptionally well. Use Opus for critical analysis, Sonnet for routine processing.
Code Generation
Claude and GPT-4 both excel here. Consider specialized models like Codex for specific programming tasks.
Data Analysis
Gemini's integration with data tools makes it strong for analytical workflows. GPT-4 excels at interpreting results.
Cost Considerations
Model costs vary significantly:
- Fast models: $0.50-2 per million tokens
- Balanced models: $3-15 per million tokens
- Premium models: $30-60 per million tokens
Smart routing can reduce costs by 40-70% while maintaining quality.
Configuration Best Practices
- Set appropriate temperature (0.1-0.3 for factual, 0.7-1.0 for creative)
- Use system prompts to establish context and constraints
- Configure max tokens based on expected output length
- Enable streaming for better user experience on long responses