GPT-5.2 Codex vs Qwen3 30B A3B
GPT-5.2 Codex leads the LLM Stats Score 34.6 to 17.7. Qwen3 30B A3B is 32.1x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.2 Codex leads the overall LLM Stats Score 34.6 to 17.7, ranking #81 overall.
In the 1 individual benchmarks reported for both models, Qwen3 30B A3B wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 30B A3B is roughly 32.1x 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 34.6 and ranks #81 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 30B A3B
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 32.1x 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 · 8 for Qwen3 30B A3B
GPT-5.2 Codex outperforms in 0 benchmarks, while Qwen3 30B A3B is better at 0 benchmarks.
Both models are evenly matched across the benchmarks.
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 17.5x more expensive than Qwen3 30B A3B ($0.10/1M tokens).
For output processing, GPT-5.2 Codex ($14.00/1M tokens) is 46.7x more expensive than Qwen3 30B A3B ($0.30/1M tokens).
In conclusion, GPT-5.2 Codex is more expensive than Qwen3 30B A3B.*
* 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 30B A3B's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.2 Codex supports multimodal inputs, whereas Qwen3 30B A3B 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
Qwen3 30B A3B
License
Usage and distribution terms
GPT-5.2 Codex is licensed under a proprietary license, while Qwen3 30B A3B 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 30B A3B was released on 2025-04-29.
GPT-5.2 Codex is 9 months newer than Qwen3 30B A3B.
Jan 14, 2026
7 months ago
8mo newerApr 29, 2025
1.3 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-5.2 Codex is available from OpenAI. Qwen3 30B A3B is available from DeepInfra, Novita, Fireworks.
GPT-5.2 Codex
Qwen3 30B A3B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.2 Codex and Qwen3 30B A3B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.2 Codex vs Qwen3 30B A3B.