The Ultimate AI Model Comparison - 2025 Edition
OpenAI
Anthropic
| Specification | GPT-5 | Claude Sonnet 4 |
|---|---|---|
| Release Date | August 2025 | May 2025 |
| Context Window | 272,000 tokens | 1,000,000 tokens (200K standard) |
| Output Limit | 128,000 tokens | 64,000 tokens |
| Coding Performance | Excellent front-end generation | 72.7% SWE-bench (state-of-the-art) |
| Response Speed | Adaptive (fast/deliberate) | Fast latency |
| Multimodal Support | Yes | Yes |
| Knowledge Cutoff | 2025 (latest training) | March 2025 (reliable to Jan 2025) |
| API Access | OpenAI API, Microsoft integration | Anthropic API, AWS Bedrock, Google Vertex AI |
| Enterprise Security | AES-256, TLS 1.2+ | Enterprise-grade security |
| Special Features | Dynamic reasoning, personality traits | Interleaved thinking, refusal stop reasons |
Both models excel in different areas. Choose GPT-5 for front-end development, Microsoft ecosystem integration, and dynamic reasoning tasks. Choose Claude Sonnet 4 for large codebase analysis, autonomous agents, and high-volume enterprise applications requiring massive context windows. The "winner" depends entirely on your specific use case and requirements.
Claude Sonnet 4 leads in pure coding benchmarks with its 72.7% SWE-bench score, representing state-of-the-art performance in software engineering tasks. It excels at debugging larger repositories and navigating complex codebases, typically reducing errors from 20% to near zero. The model's 1M token context window allows it to process entire codebases with over 75,000 lines of code in a single request.
GPT-5, while not benchmarked on SWE-bench, shows particular strength in front-end generation and UI creation with minimal prompting. It produces high-quality code and demonstrates improvements in complex front-end generation, making it ideal for web development and user interface creation.
Claude Sonnet 4's 1M token context window (5x larger than its previous 200K limit) is a game-changer for processing large documents, research papers, and extensive codebases. This massive context allows for unprecedented document analysis and code understanding capabilities.
GPT-5 offers 272K input tokens, which while smaller than Claude's maximum, still provides substantial context for most applications. However, GPT-5 compensates with a higher output limit of 128K tokens compared to Claude's 64K, making it better for generating longer responses and documents.
GPT-5 introduces dynamic reasoning adaptation, automatically choosing between rapid responses for simple queries and more deliberate reasoning for complex problems. This removes the traditional trade-off between speed and depth, optimizing performance based on query complexity.
Claude Sonnet 4 maintains fast response latency while handling massive context windows efficiently. Its interleaved thinking capabilities allow for more sophisticated reasoning processes, particularly beneficial for autonomous AI agents and complex problem-solving tasks.
GPT-5 has been deeply integrated into Microsoft's consumer and developer products, trained on Azure infrastructure. It offers enterprise security features including AES-256 encryption for stored data and TLS 1.2+ for data in transit, making it ideal for Microsoft-centric enterprise environments.
Claude Sonnet 4 provides broader platform availability through the Anthropic API, Amazon Bedrock, and Google Cloud's Vertex AI. This multi-cloud approach offers more flexibility for enterprises with diverse infrastructure requirements.