What are the differences between GPT-4, Claude, and Gemini?

Great question! Here's a comprehensive comparison:

GPT-4 (OpenAI)

• Context window: 8K (standard), 32K, 128K (Turbo)
• Cost: $0.03/1K input tokens, $0.06/1K output (GPT-4 Turbo)
• Strengths: Best for creative writing and general knowledge. Strong reasoning capabilities. Excellent function calling. Large ecosystem and community.
• Weaknesses: Can be verbose. Knowledge cutoff (training data ends April 2023). Slower than competitors.

Claude 3 (Anthropic)

• Context window: 200K tokens (!)
• Cost: $0.015/1K input, $0.075/1K output (Claude 3 Opus)
• Strengths: Massive context window (entire books). More "honest" - admits uncertainty more readily. Better at following complex instructions. Strong safety features.
• Weaknesses: Smaller ecosystem than GPT-4. Can be overly cautious/refuse benign requests. Less creative than GPT-4.

Gemini Pro (Google)

• Context window: 32K tokens (1M experimental)
• Cost: $0.00025/1K input, $0.0005/1K output (Pro)
• Strengths: Cheapest option by far. Multimodal (text, images, video). Fast inference. Integrated with Google ecosystem.
• Weaknesses: Newer, less proven in production. Smaller community and fewer resources. Quality can be inconsistent.

Decision Framework:

Choose GPT-4 if:

• You need the most reliable, well-tested option
• Creative writing is important
• You want extensive community support
• Budget is not the primary concern

Choose Claude if:

• You need huge context windows (long documents)
• Safety and reliability are critical
• You want more "truthful" responses
• You're okay with slightly higher output costs

Choose Gemini if:

• Cost is a major factor
• You need multimodal capabilities
• You're already in Google ecosystem
• You're okay with being an early adopter

My Recommendation: Start with GPT-4 Turbo for most applications. It's the safe choice with the best ecosystem. Once you understand your specific needs, experiment with Claude (for long context) or Gemini (for cost savings).

Pro tip: Use different models for different tasks: GPT-4 for complex reasoning, Claude for document analysis, Gemini for high-volume, simple tasks. Many production apps use a hybrid approach!