GPT-5.2 Codex
vgpt-5-2-codex-2025-12-11OpenAI
OpenAI's specialized coding model built on GPT-5.2 with 56.4% SWE-bench Pro (state-of-the-art), 64% Terminal-bench 2.0, native code compaction, and enhanced cybersecurity capabilities.
Trust Vector Analysis
Dimension Breakdown
🚀Performance & Reliability+
State-of-the-art coding model: 56.4% SWE-bench Pro, 82.1% SWE-bench Verified, 64% Terminal-bench 2.0. Native code compaction for clean outputs.
Professional and enterprise coding benchmarks
Reasoning benchmarks optimized for code-related tasks
General knowledge testing
Code consistency and format testing
Median latency for code generation
95th percentile response time
Official specification
🛡️Security+
Enhanced cybersecurity capabilities for secure code generation. Specialized for identifying and avoiding code vulnerabilities.
Testing against code-focused injection attacks
Adversarial prompt testing
Code-specific data handling review
Security-focused code output testing
API security review
🔒Privacy & Compliance+
Standard OpenAI privacy. Important for code: ensure proprietary code handling policies are understood.
Enterprise documentation review
Policy review
Terms review
Data protection review
Certification verification
Enterprise feature review
👁️Trust & Transparency+
Strong code explainability with native documentation generation. Enhanced for secure code practices.
Code explainability assessment
Code accuracy and compilation testing
Code generation bias assessment
Code confidence expression
Documentation review
Training data disclosure review
Code safety mechanism review
⚙️Operational Excellence+
Excellent developer experience with native code compaction and IDE integrations. Industry-leading code tooling.
API design review
SDK review
Versioning review
Observability review
Support assessment
Ecosystem analysis
- +State-of-the-art coding: 56.4% SWE-bench Pro (best available)
- +82.1% SWE-bench Verified (exceeds Claude Opus 4.5)
- +64% Terminal-bench 2.0 (industry-leading CLI)
- +Native code compaction for clean, formatted output
- +Enhanced cybersecurity for secure code generation
- +400K context for full codebase analysis
- +IDE integrations and developer tooling
- !Specialized for coding - reduced general capabilities
- !Not suitable for non-code tasks
- !Same pricing as GPT-5.2
- !Not HIPAA eligible
- !30-day data retention
Use Case Ratings
code generation
State-of-the-art: 56.4% SWE-bench Pro, 82.1% SWE-bench Verified. Native compaction for clean code.
customer support
Specialized for coding, not optimized for general customer support.
content creation
Good for technical documentation, not optimized for general content.
data analysis
Strong for code-based data analysis and scripting.
research assistant
Excellent for code research, limited for general research.
legal compliance
Not designed for legal work. Use general-purpose models.
healthcare
Not suitable for healthcare applications.
financial analysis
Good for quantitative coding, limited for general finance.
education
Excellent for teaching programming and code review.
creative writing
Specialized for code, not creative writing.