GPT-5.2 Codex vs Qwen3 VL 235B A22B Instruct
GPT-5.2 Codex leads the LLM Stats Score 34.4 to 24.7. Qwen3 VL 235B A22B Instruct is 13.0x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.2 Codex leads the overall LLM Stats Score 34.4 to 24.7, ranking #90 overall.
On price, Qwen3 VL 235B A22B Instruct is roughly 13.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.2 Codex also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.2 Codex
- overall performance matters — it scores 34.4 and ranks #90 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Jan 2026
Choose Qwen3 VL 235B A22B Instruct
- cost matters — it's about 13.0x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
3 reported for GPT-5.2 Codex · 50 for Qwen3 VL 235B A22B Instruct
GPT-5.2 Codex and Qwen3 VL 235B A22B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.2 Codex ($1.75/1M tokens) is 8.8x more expensive than Qwen3 VL 235B A22B Instruct ($0.20/1M tokens).
For output processing, GPT-5.2 Codex ($14.00/1M tokens) is 15.9x more expensive than Qwen3 VL 235B A22B Instruct ($0.88/1M tokens).
In conclusion, GPT-5.2 Codex is more expensive than Qwen3 VL 235B A22B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.2 Codex accepts 400,000 input tokens compared to Qwen3 VL 235B A22B Instruct's 262,144 tokens. Qwen3 VL 235B A22B Instruct can generate longer responses up to 262,144 tokens, while GPT-5.2 Codex is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.2 Codex and Qwen3 VL 235B A22B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.2 Codex
Qwen3 VL 235B A22B Instruct
License
Usage and distribution terms
GPT-5.2 Codex is licensed under a proprietary license, while Qwen3 VL 235B A22B 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 Qwen3 VL 235B A22B Instruct was released on 2025-09-22.
GPT-5.2 Codex is 4 months newer than Qwen3 VL 235B A22B Instruct.
Jan 14, 2026
8 months ago
3mo newerSep 22, 2025
11 months 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-5.2 Codex is available from OpenAI. Qwen3 VL 235B A22B Instruct is available from DeepInfra, Novita.
GPT-5.2 Codex
Qwen3 VL 235B A22B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.2 Codex and Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.2 Codex vs Qwen3 VL 235B A22B Instruct.