GPT-4o vs Claude 4 Opus

1. High-intelligence, general-purpose model

• Strong reasoning, creativity, summarization, and problem-solving.
• Great balance of speed, accuracy, and cost.

2. Multimodal input support

• Accepts text + image inputs for visual reasoning, extraction, or description.
• Output is text only, making it predictable for production.

3. Excellent for structured and unstructured tasks

• Performs well on Q&A, writing, analysis, classification, chat, and planning.
• Supports Structured Outputs, making it suitable for deterministic workflows.

4. Strong tool-use capabilities

• Supports function calling, API orchestration, and tool-augmented workflows.
• Integrates well with assistants, batch operations, and automation pipelines.

5. Large context for complex tasks

• 128K context allows multi-document reasoning, multi-step conversations, and large input payloads.

6. Production-ready reliability

• Stable outputs, predictable behaviors, and broad modality coverage.
• Supported across all major API endpoints.

7. Lower latency than o-series reasoning models

• Faster responses due to no dedicated reasoning step.
• Ideal for interactive or near-real-time applications.

8. Fine-tuning and distillation supported

• Enables specialization for domain-specific tasks.
• Distillation helps create smaller, efficient custom models.

• Highest capability in the family: described as “our most powerful model yet” by Anthropic.
• Exceptional at long-running tasks requiring thousands of steps and sustained focus (e.g., continuous codebase work for hours).
• Excellent performance on benchmarks: e.g., SWE-bench 72.5 % and Terminal-bench 43.2 %.
• Designed for complex agentic workflows, deep reasoning, tool use, and large context windows.
• Placed under a higher safety classification (ASL-3) due to its frontier capability and risk profile.