LLM ComparisonGPT-5.2GPT-5 Codex

GPT-5.2 vs GPT-5 Codex

Compare GPT-5.2 and GPT-5 Codex. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.2GPT-5 Codex
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens400,000 tokens
Input Cost
$1.75/ 1M tokens
$1.25/ 1M tokens
Output Cost
$14.00/ 1M tokens
$10.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.2

OpenAI

1. Advanced Reasoning for Diverse Domains

  • Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.

2. Multi-Modal & Long-Form Capabilities

  • Handles both text and image inputs, producing text output.
  • Allows up to 128 k output tokens for lengthy responses.

3. Large Context & Updated Knowledge

  • 400 k token context window accommodates extensive codebases or documents.
  • Knowledge cut-off of Aug 31 2025 keeps it current with recent developments.

GPT-5 Codex

OpenAI

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.

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