Model Comparison

Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 32B Thinking

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

16 benchmarks

Qwen3-235B-A22B-Thinking-2507 outperforms in 15 benchmarks (AIME 2025, Arena-Hard v2, BFCL-v3, Creative Writing v3, GPQA, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 32B Thinking is better at 0 benchmarks.

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

202.0B diff

Qwen3-235B-A22B-Thinking-2507 has 202.0B more parameters than Qwen3 VL 32B Thinking, making it 612.1% larger.

Qwen3-235B-A22B-Thinking-2507

235.0Bparameters

Qwen3 VL 32B Thinking

33.0Bparameters

235.0B

Qwen3-235B-A22B-Thinking-2507

33.0B

Qwen3 VL 32B Thinking

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).

Qwen3-235B-A22B-Thinking-2507

Input262,144 tokens

Output131,072 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Thinking supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

Qwen3 VL 32B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3-235B-A22B-Thinking-2507

Text

Images

Audio

Video

Qwen3 VL 32B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Qwen3 VL 32B Thinking

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 Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 2 months newer than Qwen3-235B-A22B-Thinking-2507.

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

9 months ago

Qwen3 VL 32B Thinking

Sep 22, 2025

7 months ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Qwen3-235B-A22B-Thinking-2507

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher AIME 2025 score (92.3% vs 83.7%)

Higher Arena-Hard v2 score (79.7% vs 60.5%)

Higher BFCL-v3 score (71.9% vs 71.7%)

Higher Creative Writing v3 score (86.1% vs 83.3%)

Higher GPQA score (81.1% vs 73.1%)

Higher Include score (81.0% vs 76.3%)

Higher LiveBench 20241125 score (78.4% vs 74.7%)

Higher LiveCodeBench v6 score (74.1% vs 65.6%)

Higher MMLU-Pro score (84.4% vs 82.1%)

Higher MMLU-ProX score (81.0% vs 77.2%)

Higher MMLU-Redux score (93.8% vs 91.9%)

Higher Multi-IF score (80.6% vs 78.0%)

Higher PolyMATH score (60.1% vs 52.0%)

Higher SuperGPQA score (64.9% vs 59.0%)

Higher WritingBench score (88.3% vs 86.2%)

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3-235B-A22B-Thinking-2507	Qwen3 VL 32B Thinking

FAQ

Common questions about Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 32B Thinking.

Which is better, Qwen3-235B-A22B-Thinking-2507 or Qwen3 VL 32B Thinking?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team and Qwen3 VL 32B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3-235B-A22B-Thinking-2507 compare to Qwen3 VL 32B Thinking in benchmarks?

Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for Qwen3-235B-A22B-Thinking-2507 and Qwen3 VL 32B Thinking?

Qwen3-235B-A22B-Thinking-2507 supports 262K tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3-235B-A22B-Thinking-2507 and Qwen3 VL 32B Thinking?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.