Model Comparison
Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 32B InstructWhich is better in 2026?
Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.
Verdict: Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 32B Instruct — which is better?
Qwen3-235B-A22B-Thinking-2507 (by Alibaba Cloud / Qwen Team) and Qwen3 VL 32B Instruct (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.
Qwen3-235B-A22B-Thinking-2507 outperforms in 16 benchmarks (AIME 2025, Arena-Hard v2, BFCL-v3, Creative Writing v3, GPQA, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 32B Instruct is better at 0 benchmarks. Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.
Choose Qwen3-235B-A22B-Thinking-2507 if…
- you want the strongest raw capability — it leads on 16 of 16 shared benchmarks
Choose Qwen3 VL 32B Instruct if…
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3-235B-A22B-Thinking-2507 outperforms in 16 benchmarks (AIME 2025, Arena-Hard v2, BFCL-v3, Creative Writing v3, GPQA, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 32B Instruct is better at 0 benchmarks.
Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Qwen3-235B-A22B-Thinking-2507 has 202.0B more parameters than Qwen3 VL 32B Instruct, making it 612.1% larger.
Context Window
Maximum input and output token capacity
Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Qwen3 VL 32B Instruct supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.
Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3-235B-A22B-Thinking-2507
Qwen3 VL 32B Instruct
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25, while Qwen3 VL 32B Instruct was released on 2025-09-22.
Qwen3 VL 32B Instruct is 2 months newer than Qwen3-235B-A22B-Thinking-2507.
Jul 25, 2025
11 months ago
Sep 22, 2025
9 months ago
1mo newerKnowledge 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
Qwen3-235B-A22B-Thinking-2507
View detailsAlibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Qwen3-235B-A22B-Thinking-2507 and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 32B Instruct.