1. Advanced reasoning capability

• Designed for multi-step thinking across text, code, and visual inputs.
• Excels at math, science, logic puzzles, and complex analytical workflows.

2. Strong performance across domains

• Highly capable in technical writing, data analysis, and structured problem-solving.
• Useful for research, engineering tasks, and intricate instruction-following.

3. Visual reasoning support

• Accepts image inputs, enabling tasks such as diagram analysis, chart interpretation, and visual logic assessments.

4. High output capacity

• Up to 100,000 output tokens, supporting long-form content, technical breakdowns, and multi-part solutions.

5. Excellent instruction following

• Produces detailed, step-by-step responses for tasks requiring precision and clarity.
• Ideal for educational explanations, system design reasoning, and code walkthroughs.

6. Large 200K context window

• Handles long documents, multi-file reasoning, or extended conversations with minimal loss of context.

7. Broad API support

• Works with Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, Image Generation, and more.
• Supports streaming and function calling for advanced workflows.

8. Positioned as a legacy reasoning model

• Remains extremely capable but formally succeeded by GPT-5, which offers stronger reasoning and performance.

1. Strong enterprise-grade reasoning

• Built for deep logical reasoning, structured decision-making, and multi-step analysis.
• Performs exceptionally in domains requiring precision: law, finance, healthcare, and STEM.

2. Excellent at data extraction and summarization

• Optimized for structured extraction from documents, PDFs, tables, and complex text.
• Ideal for enterprise workflows like reporting, compliance automation, or knowledge mining.

3. High-performance coding capabilities

• Excels at code generation, debugging, refactoring, and explaining code.
• Competitive with top-tier coding models for multi-file, long-context code reasoning.

4. Supports function calling and structured outputs

• Integrates cleanly with agent frameworks and external tools.
• Predictable, schema-aligned responses suitable for production systems.

5. Large 131K context window

• Handles long documents, transcripts, contracts, codebases, or multi-document tasks.
• Useful for ingesting highly technical materials in one pass.

6. Efficient cost structure with cached token pricing

• Cached inputs: only $0.75 / 1M tokens, enabling large-scale systems.
• Encourages reuse for powerful retrieval-augmented workflows.

7. Enterprise reliability and availability

• Supported across multiple regions (us-east-1, eu-west-1).
• Consistent rate limits: 600 requests/min.
• Suitable for production-grade apps with stability requirements.

8. Supports advanced search capabilities

• Optional Live Search add-on for real-time knowledge retrieval.
• Pricing: $25 per 1K sources.