Model Comparison
GPT-5.3 Codex vs Qwen3-CoderWhich is better in 2026?
Comparing GPT-5.3 Codex and Qwen3-Coder across benchmarks, pricing, and capabilities.
Verdict: GPT-5.3 Codex vs Qwen3-Coder — which is better?
GPT-5.3 Codex (by OpenAI) and Qwen3-Coder (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Qwen3-Coder is roughly 26.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.3 Codex also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-5.3 Codex if…
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Feb 2026
Choose Qwen3-Coder if…
- cost matters — it's about 26.7x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5.3 Codex and Qwen3-Coderdon'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
For input processing, GPT-5.3 Codex ($1.75/1M tokens) is 9.7x more expensive than Qwen3-Coder ($0.18/1M tokens).
For output processing, GPT-5.3 Codex ($14.00/1M tokens) is 77.8x more expensive than Qwen3-Coder ($0.18/1M tokens).
In conclusion, GPT-5.3 Codex is more expensive than Qwen3-Coder.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.3 Codex accepts 400,000 input tokens compared to Qwen3-Coder's 256,000 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while GPT-5.3 Codex is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
GPT-5.3 Codex supports multimodal inputs, whereas Qwen3-Coder does not.
GPT-5.3 Codex can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.3 Codex
Qwen3-Coder
License
Usage and distribution terms
GPT-5.3 Codex is licensed under a proprietary license, while Qwen3-Coder 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-5.3 Codex was released on 2026-02-05, while Qwen3-Coder was released on 2025-01-01.
GPT-5.3 Codex is 13 months newer than Qwen3-Coder.
Feb 5, 2026
5 months ago
1.1yr newerJan 1, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-5.3 Codex is available from OpenAI. Qwen3-Coder is available from DeepInfra, Fireworks.
GPT-5.3 Codex
Qwen3-Coder
Outputs Comparison
Key Takeaways
Qwen3-Coder
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-5.3 Codex and Qwen3-Coder side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-5.3 Codex vs Qwen3-Coder.