Model Comparison

Gemma 3 27B vs Qwen3 VL 32B Thinking

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Gemma 3 27B outperforms in 1 benchmarks (IFEval), while Qwen3 VL 32B Thinking is better at 6 benchmarks (AI2D, GPQA, MathVista-Mini, MMLU-Pro, MMMU (val), SimpleQA).

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.

Sat May 23 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

6.0B diff

Qwen3 VL 32B Thinking has 6.0B more parameters than Gemma 3 27B, making it 22.2% larger.

Gemma 3 27B

27.0Bparameters

Qwen3 VL 32B Thinking

33.0Bparameters

27.0B

Gemma 3 27B

33.0B

Qwen3 VL 32B Thinking

Context Window

Maximum input and output token capacity

Only Gemma 3 27B specifies input context (131,072 tokens). Only Gemma 3 27B specifies output context (131,072 tokens).

Gemma 3 27B

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Sat May 23 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 27B and Qwen3 VL 32B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 3 27B

Text

Images

Audio

Video

Qwen3 VL 32B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Gemma 3 27B is licensed under Gemma, while Qwen3 VL 32B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 3 27B

Gemma

Open weights

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3 27B was released on 2025-03-12, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 6 months newer than Gemma 3 27B.

Gemma 3 27B

Mar 12, 2025

1.2 years ago

Qwen3 VL 32B Thinking

Sep 22, 2025

8 months ago

6mo 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Gemma 3 27B

View details

Google

Larger context window (131,072 tokens)

Higher IFEval score (90.4% vs 87.8%)

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Higher AI2D score (88.9% vs 84.5%)

Higher GPQA score (73.1% vs 42.4%)

Higher MathVista-Mini score (85.9% vs 67.6%)

Higher MMLU-Pro score (82.1% vs 67.5%)

Higher MMMU (val) score (78.1% vs 64.9%)

Higher SimpleQA score (55.4% vs 10.0%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemma 3 27B	Qwen3 VL 32B Thinking

FAQ

Common questions about Gemma 3 27B vs Qwen3 VL 32B Thinking.

Which is better, Gemma 3 27B or Qwen3 VL 32B Thinking?

Qwen3 VL 32B Thinking significantly outperforms across most benchmarks. Gemma 3 27B is made by Google 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 Gemma 3 27B compare to Qwen3 VL 32B Thinking in benchmarks?

Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%. 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 Gemma 3 27B and Qwen3 VL 32B Thinking?

Gemma 3 27B supports 131K 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 Gemma 3 27B and Qwen3 VL 32B Thinking?

Key differences include licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 27B and Qwen3 VL 32B Thinking?

Gemma 3 27B is developed by Google and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.