GPT-5.1 Codex vs Claude 4.1 Opus

Compare GPT-5.1 Codex and Claude 4.1 Opus. Find out which one is better for your use case.

Model Comparison

FeatureGPT-5.1 CodexClaude 4.1 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost$1.25 / 1M tokens$15.00 / 1M tokens
Output Cost$10.00 / 1M tokens$75.00 / 1M tokens

Strengths & Best Use Cases

GPT-5.1 Codex

1. Purpose-Built for Agentic Coding

  • Designed specifically for environments where the model acts as an autonomous or semi-autonomous coding agent.
  • Optimized for multi-step reasoning in code tasks such as planning, refactoring, debugging, file generation, and tool coordination.

2. Enhanced Coding Intelligence

  • Extends GPT-5.1's advanced reasoning capabilities to handle complex software architecture decisions.
  • Better accuracy in code generation across languages (JavaScript, Python, TypeScript, Go, Rust, etc.).
  • Produces cleaner, more idiomatic code aligned with modern frameworks and best practices.

3. Superior Tool Use & Code Navigation

  • Excels at reading, understanding, and transforming multi-file codebases.
  • Works well with Codex workflows that simulate real developer tooling.
  • Strong at following function signatures, constraints, and code patterns within an existing project.

4. Long-Range Context Awareness

  • 400,000-token context window enables the model to ingest large repositories or multiple files simultaneously.
  • Supports deep analysis of project structures, dependencies, and cross-file logic.

5. Multi-Modal Development Capabilities

  • Accepts text + image input and output — suitable for tasks like:
    • Reading UI mockups or screenshots to generate code
    • Understanding architectural diagrams
    • Reviewing images of whiteboard sessions

6. Agentic Workflow Optimization

  • Built to manage longer chains of thought and execution typically required in:
    • Automated code repair
    • Project bootstrapping
    • Linting and migration tasks
    • Long-running coding agents using planning + execution loops

7. Continually Updated Model Snapshot

  • Codex-specific version receives regular upgrades behind the scenes.
  • Ensures the latest coding improvements without requiring developers to update model names.

8. Reliable Instruction Following

  • Highly consistent in honoring explicit constraints:
    • Code styles
    • Folder structures
    • API contracts
    • Framework conventions

9. Broad API Support

  • Works across Chat Completions, Responses API, Realtime, Assistants, and more.
  • Ideal for apps that need live, reasoning-heavy coding agents or generative dev environments.

Claude 4.1 Opus

1. Advanced Coding Performance

  • Achieves 74.5% on SWE-bench Verified, improving the Claude family's state-of-the-art coding abilities.

  • Stronger at:

    • Multi-file code refactoring
    • Large codebase debugging
    • Pinpointing exact corrections without unnecessary edits
  • Outperforms Opus 4 and shows gains comparable to jumps seen in past major releases.

2. Improved Agentic & Research Capabilities

  • Better at maintaining detail accuracy in long research tasks.
  • Enhanced agentic search and step-by-step problem solving.
  • Performs reliably across complex multi-turn reasoning tasks.

3. Validated by Real-World Users

  • GitHub: Better multi-file refactoring and code adjustments.
  • Rakuten Group: High precision debugging with minimal collateral changes.
  • Windsurf: One standard deviation improvement on their junior dev benchmark—similar magnitude to Sonnet 3.7 → Sonnet 4.

4. Hybrid-Reasoning Benchmark Improvements

  • Improvements across TAU-bench, GPQA Diamond, MMMLU, MMMU, AIME (with extended thinking).
  • Stronger robustness in long-context reasoning tasks.

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