GPT-5.3 Codex vs GPT-5 Pro

1. Strongest Codex Model for Agentic Engineering

• OpenAI positions GPT-5.3 Codex as its most capable agentic coding model to date.
• Built for long-horizon software engineering tasks that require planning, iteration, and reliable code transformation across files.

2. Configurable Reasoning + Multimodal Input

• Supports configurable reasoning effort from low to xhigh so teams can trade off depth against latency.
• Accepts both text and image inputs while producing text output.

3. Large Context for Real Codebases

• 400 k token context window helps it work across larger repositories, implementation plans, and supporting documentation.
• Allows up to 128 k output tokens for longer code generations, patches, and technical write-ups.

4. Current Knowledge for Modern Dev Workflows

• Knowledge cut-off of Aug 31 2025 keeps it aligned with newer frameworks, libraries, and tooling.
• Supports streaming, function calling, and structured outputs for agent-style coding workflows.

1. Highest reasoning quality in the GPT-5 family

• Uses significantly more compute to "think harder" before responding.
• Designed for the toughest reasoning tasks where answer quality matters more than speed.
• Produces more precise, reliable, and detailed outputs than standard GPT-5.

2. Advanced multi-turn reasoning via Responses API

• Available only in the Responses API to support:
  • Multi-turn internal model interactions before returning a reply.
  • Advanced control patterns (e.g., background mode for long-running jobs).
• Ideal for complex workflows, deep planning, and multi-step analysis.

3. Configured for maximum effort by default

• Always runs with reasoning.effort: 'high' (no lower-effort mode).
• Prioritizes depth and correctness over latency and cost.

4. Multimodal input

• Accepts text + image as input.
• Outputs text, with strong instruction-following and analysis capabilities.

5. Tooling and ecosystem integration

• Supports Web Search, File Search, and Image Generation (as tools).
• Supports MCP and other Responses API tooling patterns.
• Does not support Code Interpreter and does not support Computer Use, keeping focus on pure reasoning + tools.