GPT-5.2 Codex vs Claude 4.6 Opus

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. Anthropic's top model for coding and agents

• Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
• It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.

2. Strong frontier performance on real agent benchmarks

• Anthropic reports state-of-the-art results across coding and agentic evaluations.
• Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.

3. Best fit for long-horizon, high-context work

• Supports up to a 1M token context window in beta and up to 128K output tokens.
• Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.

4. Advanced reasoning controls and workflow support

• Supports adaptive thinking and the effort parameter, including the new max effort level.
• Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.