Overview & Quick Comparison
In 2025, the LLM API landscape is dominated by three major players: Claude 3.5 Sonnet from Anthropic, GPT-4o from OpenAI, and Gemini 2.5 Pro from Google. Each model offers unique strengths and trade-offs that make them suitable for different applications[1].
| Feature | Claude 3.5 Sonnet | GPT-4 Turbo | Gemini 1.5 Pro |
|---|---|---|---|
| Best For | Document analysis, Complex reasoning | Code generation, General purpose | Multimodal tasks, Large contexts |
| Context Window | 200K tokens | 128K tokens | 1M tokens |
| Input Price/1M tokens | $3.00 | $2.50 | $1.25-$2.50 |
| Output Price/1M tokens | $15.00 | $10.00-$15.00 | $10.00-$15.00 |
| Multimodal | |||
| Function Calling |
Pricing Comparison
Understanding the pricing structure of each LLM API is crucial for budgeting and cost optimization. Here's a detailed breakdown of current pricing as of 2025. Claude 3.5 Sonnet is the most expensive, GPT-4o offers mid-tier pricing, and Gemini 2.5 provides the most cost-effective option[2]:
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Blended Average* |
|---|---|---|---|
| Claude 3.5 Sonnet | $3.00 | $15.00 | $9.00 |
| GPT-4 Turbo | $2.50 | $10.00 | $6.25 |
| Gemini 1.5 Pro | $2.50 | $10.00 | $6.25 |
| Gemini 2.0 Flash | $0.10 | $0.40 | $0.25 |
*Blended average assumes 50/50 input/output ratio
Hidden Costs to Consider
- Rate limiting overages: Additional charges when exceeding rate limits
- Fine-tuning costs: GPT-4 offers fine-tuning at premium rates
- Storage costs: For conversation history and embeddings
- Egress charges: Data transfer costs on cloud platforms
Performance Benchmarks
Performance varies significantly across different tasks. Recent benchmarks show Claude 3.5 leading in coding accuracy (93.7%), GPT-4o excelling in mathematics (76.6% MATH), and Gemini 2.5 offering superior multimodal capabilities[3]:
| Model | MMLU | HumanEval | GSM8K |
|---|---|---|---|
| Claude 3.5 | 88.7% | 84.1% | 95.0% |
| GPT-4 Turbo | 86.5% | 85.4% | 94.2% |
| Gemini 1.5 | 87.9% | 83.6% | 94.8% |
Latency Considerations
- First token latency: Gemini typically fastest at 200-400ms, Claude at 300-500ms, GPT-4 at 400-600ms
- Streaming support: All three support streaming for real-time applications
- Geographic latency: Varies by region; all have global endpoints
Features & Capabilities
Context Window Comparison
Context window size determines how much information the model can process in a single request. Gemini 2.5 offers the largest context windows, making it ideal for processing extensive documents[4]:
- Gemini 1.5 Pro: 1 million tokens - Best for large document processing
- Claude 3.5 Sonnet: 200,000 tokens - Excellent for long conversations
- GPT-4 Turbo: 128,000 tokens - Good balance for most applications
Multimodal Capabilities
| Feature | Claude 3.5 | GPT-4 Turbo | Gemini 1.5 |
|---|---|---|---|
| Image Input | |||
| Image Generation | |||
| Audio Processing | |||
| Video Understanding | Limited | ||
| OCR Quality | Excellent | Excellent | Good |
Function Calling & Tool Use
All three models support function calling, but with different implementations[4]:
- Claude 3.5: Native tool use with strict schema validation
- GPT-4 Turbo: Mature function calling with extensive documentation
- Gemini 1.5: Advanced function calling with parallel execution support
Best Use Cases for Each Model
- Legal document analysis
- Academic research assistance
- Complex reasoning tasks
- Long-form content creation
- Ethical AI applications
- Code generation & debugging
- General chatbots
- API integrations
- Creative writing
- Enterprise applications
- Video content analysis
- Large document processing
- Multimodal applications
- Real-time processing
- Cost-sensitive workloads
Technical Specifications
API Rate Limits
| Model | Requests/min | Tokens/min | Concurrent Requests |
|---|---|---|---|
| Claude 3.5 Sonnet | 50-500* | 100K-1M* | 50 |
| GPT-4 Turbo | 60-5000* | 150K-2M* | 100 |
| Gemini 1.5 Pro | 60-2000* | 1M-4M* | 100 |
*Varies by tier and region
Supported Languages
All three models support multiple languages, but with varying proficiency. GPT-4o supports 50+ languages, while Gemini 2.5 offers consistent quality across 40+ languages[5]:
- Best English performance: Claude 3.5 Sonnet
- Most languages supported: GPT-4 Turbo (50+ languages)
- Best multilingual performance: Gemini 1.5 Pro (40+ languages with consistent quality)
Integration Options
- • Direct API
- • AWS Bedrock
- • Google Vertex AI
- • Anthropic Console
- • OpenAI API
- • Azure OpenAI
- • Microsoft Copilot
- • Playground
- • Google AI Studio
- • Vertex AI
- • Gemini API
- • Google Cloud
How to Choose the Right Model
Selecting the right LLM API depends on your specific requirements. Here's a decision framework:
Choose Claude 3.5 Sonnet if:
- ✓ Accuracy and factual correctness are paramount
- ✓ You need strong reasoning capabilities
- ✓ Working with sensitive or regulated content
- ✓ Long document analysis is required
Choose GPT-4 Turbo if:
- ✓ You need the most mature ecosystem
- ✓ Code generation is a primary use case
- ✓ You require extensive third-party integrations
- ✓ Fine-tuning capabilities are needed
Choose Gemini 1.5 Pro if:
- ✓ You need the largest context window
- ✓ Multimodal capabilities are essential
- ✓ Cost-efficiency is a priority
- ✓ Working with video or audio content
Access All Models with ParrotRouter
Why limit yourself to just one model? ParrotRouter provides unified access to all three models (and many more) through a single API, allowing you to:
- Automatic failover: Switch between models seamlessly if one is down
- Cost optimization: Route requests to the most cost-effective model
- A/B testing: Compare model performance in production
- Unified billing: One invoice for all your LLM usage
- No vendor lock-in: Switch models without changing code
Conclusion
Each of these LLM APIs excels in different areas. Claude 3.5 Sonnet leads in reasoning and accuracy, GPT-4 Turbo offers the best ecosystem and versatility, while Gemini 1.5 Pro provides superior multimodal capabilities and the largest context window.
The best choice depends on your specific use case, budget, and technical requirements. Consider starting with ParrotRouter to experiment with all three models and find the perfect fit for your application without committing to a single provider.
References
- [1] Kanerika. "ChatGPT vs Gemini vs Claude: Comprehensive Comparison" (2025)
- [2] DataStudios. "ChatGPT vs Google Gemini vs Anthropic Claude: Full Report Mid-2025" (2025)
- [3] Creator Economy. "ChatGPT vs Claude vs Gemini: Best AI Model for Each Use Case 2025" (2025)
- [4] TruInc. "ChatGPT-4o vs Gemini vs Claude 3.5: A Comparative Guide" (2025)
- [5] Pieces. "How to Use GPT-4o, Gemini 1.5 Pro, and Claude 3.5 Sonnet" (2025)
- [4] Evolution AI. "Claude 3.5 Sonnet vs GPT-4o vs Gemini 1.5 Pro—A Comprehensive Comparison" (2024)
- [5] Bind AI. "Gemini 1.5 Pro vs Claude 3.5 Sonnet: Which is Best for Coding?" (2024)
- [6] Vantage. "GPT-4o mini vs Gemini 1.5 Flash vs Claude 3 Haiku: Cost Comparison" (2024)
- [7] Pieces. "How to Use GPT-4o, Gemini 1.5 Pro, and Claude 3.5 Sonnet Free" (2024)