GPT-5.2 vs o1

1. Advanced Reasoning for Diverse Domains

• Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.

2. Multi-Modal & Long-Form Capabilities

• Handles both text and image inputs, producing text output:contentReference[oaicite:1]{index=1}.
• Allows up to 128 k output tokens for lengthy responses:contentReference[oaicite:2]{index=2}.

3. Large Context & Updated Knowledge

• 400 k token context window accommodates extensive codebases or documents:contentReference[oaicite:3]{index=3}.
• Knowledge cut-off of Aug 31 2025 keeps it current with recent developments:contentReference[oaicite:4]{index=4}.

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.