Model Comparison
GPT-5.2 Codex vs Qwen2.5-Coder 7B Instruct
Comparing GPT-5.2 Codex and Qwen2.5-Coder 7B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5.2 Codex and Qwen2.5-Coder 7B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Context Window
Maximum input and output token capacity
Only GPT-5.2 Codex specifies input context (400,000 tokens). Only GPT-5.2 Codex specifies output context (128,000 tokens).
Input Capabilities
Supported data types and modalities
GPT-5.2 Codex supports multimodal inputs, whereas Qwen2.5-Coder 7B Instruct does not.
GPT-5.2 Codex can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.2 Codex
Qwen2.5-Coder 7B Instruct
License
Usage and distribution terms
GPT-5.2 Codex is licensed under a proprietary license, while Qwen2.5-Coder 7B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5.2 Codex was released on 2026-01-14, while Qwen2.5-Coder 7B Instruct was released on 2024-09-19.
GPT-5.2 Codex is 16 months newer than Qwen2.5-Coder 7B Instruct.
Jan 14, 2026
3 months ago
1.3yr newerSep 19, 2024
1.6 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
Qwen2.5-Coder 7B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about GPT-5.2 Codex vs Qwen2.5-Coder 7B Instruct