GPT-5.5 vs GPT-5 Codex

1. Strongest Agentic Coding Model

• State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
• Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.

2. Higher Intelligence at GPT-5.4 Latency

• Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
• Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.

3. Powerful for Knowledge Work & Computer Use

• Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
• Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.

4. Scientific Research Co-Scientist

• Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
• Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.

1. Purpose-Built for Agentic Coding

• Optimized specifically for scenarios where the model must act as an autonomous or semi-autonomous coding agent.
• Tailored for Codex workflows such as planning, editing, debugging, and multi-step tool-driven code tasks.

2. Advanced Coding Reasoning

• Extends GPT-5's higher reasoning mode to better handle complex software logic and multi-file dependencies.
• Produces more accurate, structured, and maintainable code across modern programming languages.

3. Strong Tool Use in Developer-Like Environments

• Designed for Codex's agent environment, enabling the model to:
  • Read and modify files
  • Follow function signatures and API contracts
  • Navigate codebases with awareness of context and structure

4. Large Context Window for Full-Project Understanding

• 400,000-token context allows ingestion of:
  • Entire repositories
  • Multiple files at once
  • Architectural descriptions
• Enables long-range reasoning across codebases rather than isolated snippets.

5. Multimodal Capability for Development Tasks

• Accepts text and image as input (great for screenshots of error logs, UI mocks, whiteboards).
• Outputs text only, focusing its output precision on code, reasoning, and documentation.

6. Continuous Snapshot Updates

• The underlying model version is regularly upgraded behind the scenes.
• Ensures developers always use the best coding-enhanced GPT-5 variant without changing model names.

7. Reliable Instruction Following

• Very strong adherence to constraints like:
  • File/folder structure requirements
  • Framework conventions
  • Naming patterns
  • Linting rules
• Makes it suitable for production coding agents.

8. Broad API Integration

• Available only in the Responses API, giving you:
  • Streaming
  • Structured outputs
  • Function calling
• Allows creation of interactive coding tools and agent workflows with tight model control.