Qwen3.5-397B-A17B vs GPT-5.3 Codex Comparison
Comparing Qwen3.5-397B-A17B and GPT-5.3 Codex across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.5-397B-A17B outperforms in 0 benchmarks, while GPT-5.3 Codex is better at 1 benchmark (Terminal-Bench 2.0).
GPT-5.3 Codex significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Context Window
Maximum input and output token capacity
Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).
Input Capabilities
Supported data types and modalities
Both Qwen3.5-397B-A17B and GPT-5.3 Codex support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3.5-397B-A17B
GPT-5.3 Codex
License
Usage and distribution terms
Qwen3.5-397B-A17B is licensed under Apache 2.0, while GPT-5.3 Codex uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Qwen3.5-397B-A17B was released on 2026-02-16, while GPT-5.3 Codex was released on 2026-02-05.
Qwen3.5-397B-A17B is 0 month newer than GPT-5.3 Codex.
Feb 16, 2026
4 weeks ago
1w newerFeb 5, 2026
1 months 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
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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