o1 vs Claude 4.5 Sonnet

1. Full-scale reasoning model

• Uses reinforcement learning to generate long internal chains of thought.
• Suitable for tasks requiring deep logic, multi-step planning, and rich analytical reasoning.

2. Strong performance across domains

• Excellent at math, science, coding, and structured analytical work.
• Handles multi-step workflows and complex problem-solving with high consistency.

3. High output capacity (100K tokens)

• Enables long, detailed explanations, large documents, and multi-part analyses.

4. Image-understanding capable

• Accepts text + image inputs for visual reasoning and mixed-modality tasks.
• Output is text only, optimized for clear explanations.

5. Advanced API compatibility

• Works with Chat Completions, Responses, Realtime, Assistants, and more.
• Supports streaming, function calling, and structured outputs.

6. Stable long-context performance

• 200K-token context window supports large files, multi-document analysis, and extended conversations.

7. Designed for correctness-oriented workloads

• Prioritizes rigorous reasoning over speed.
• Useful in auditing, verification, scientific thinking, policy analysis, and legal-style reasoning.

8. Powerful but expensive

• High token costs make it suitable for selective, mission-critical reasoning rather than high-volume usage.

1. Best-in-class coding performance

• #1 on SWE-bench Verified (77.2% standard, 82.0% high-compute).
• Excels at debugging, architecture, and multi-file code generation.
• Maintains coherence for extremely long tasks (30+ hours).

2. State-of-the-art computer use & agents

• Leads OSWorld at 61.4%.
• Strongest model for agentic workflows, multi-step tool use, and real computer control.
• Powering Claude Code, the new Claude Agent SDK, and Chrome agent actions.

3. Advanced reasoning & math

• Large improvements across reasoning-heavy benchmarks (AIME, MMMLU, τ2-bench, Terminal-Bench).
• Deep multi-step reasoning with extended or interleaved thinking.

4. High alignment & safety

• Most aligned Claude model to date with reduced deception, hallucinations, sycophancy, and harmful compliance.
• Strong protections against prompt injection for agentic tasks (ASL-3 safeguards).

5. Domain-expert performance

• Notable gains in finance, law, medicine, and STEM tasks.
• Trusted by early customers for long-context legal analysis, multi-file engineering, security research, and red-teaming.