GPT-5.2 Codex vs Gemini 3 Pro

1. Optimized for Long-Horizon Coding Tasks

• OpenAI describes GPT-5.2 Codex as a highly intelligent coding model built for long-horizon, agentic coding work.
• Well suited to planning, refactoring, debugging, and multi-step implementation flows inside real codebases.

2. Adjustable Reasoning for Coding Work

• Supports configurable reasoning effort from low to xhigh depending on speed and quality needs.
• Accepts both text and image inputs while producing text output.

3. Large Context + Long Output

• 400 k token context window supports broad repository understanding and larger working sets.
• Allows up to 128 k output tokens for longer patches, code generation, and technical explanations.

4. Up-to-Date Model Snapshot

• Knowledge cut-off of Aug 31 2025 keeps it current with newer tools and frameworks.
• Supports streaming, function calling, and structured outputs for tool-driven coding workflows.

1. State-of-the-art reasoning

• Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
• Excels at long-horizon, multi-step workflows and deep logical interpretation.

2. World-leading multimodal capabilities

• Natively understands text, images, videos, audio, and code.
• Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.

3. Exceptional coding + agentic workflows

• Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
• Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.

4. Powerful for long-context tasks

• Effective at 128K-1M context windows with high retrieval accuracy.
• Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.

5. Strong information synthesis and interpretation

• Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
• Excellent at combining multimodal inputs into coherent, concise answers.

6. High reliability for enterprise tasks

• Benchmarks show superior factuality, grounding, and parametric knowledge.
• Strong multilingual accuracy and global commonsense performance.

7. Optimized for production agents

• Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
• Works across coding, research, creative workflows, UI generation, and data-heavy applications.