GPT-5.2 Codex vs QwQ-Plus

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. Deep reasoning specialization

• Competes with DeepSeek-R1 full-performance levels.
• Excellent for math, proofs, symbolic logic.

2. Strong code reasoning

• Top-tier LiveCodeBench performance.

3. Chain-of-thought supported

• Up to 32K reasoning tokens.

4. Reliable structured outputs

• Consistent on difficult multi-step problems.