Model Comparison

Gemma 2 9B vs Qwen3 VL 30B A3B ThinkingWhich is better in 2026?

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

Verdict: Gemma 2 9B vs Qwen3 VL 30B A3B Thinking — which is better?

Gemma 2 9B (by Google) and Qwen3 VL 30B A3B Thinking (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.

Gemma 2 9B outperforms in 0 benchmarks, while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (MMLU). Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

Choose Gemma 2 9B if…

  • you are already invested in the Google ecosystem

Choose Qwen3 VL 30B A3B Thinking if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Sep 2025

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemma 2 9B outperforms in 0 benchmarks, while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (MMLU).

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

21.8B diff

Qwen3 VL 30B A3B Thinking has 21.8B more parameters than Gemma 2 9B, making it 235.5% larger.

Google
Gemma 2 9B
9.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
9.2B
Gemma 2 9B
31.0B
Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 30B A3B Thinking specifies input context (131,072 tokens). Only Qwen3 VL 30B A3B Thinking specifies output context (32,768 tokens).

Google
Gemma 2 9B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Gemma 2 9B does not.

Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 9B

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 9B is licensed under Gemma, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.

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

Gemma 2 9B

Gemma

Open weights

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 2 9B was released on 2024-06-27, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

Qwen3 VL 30B A3B Thinking is 15 months newer than Gemma 2 9B.

Gemma 2 9B

Jun 27, 2024

2.0 years ago

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

9 months ago

1.2yr 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

No standout differentiators in the data we have for this pair.

Alibaba Cloud / Qwen Team

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)
Supports multimodal inputs
Higher MMLU score (87.6% vs 71.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 9B
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking

FAQ

Common questions about Gemma 2 9B vs Qwen3 VL 30B A3B Thinking.

Which is better, Gemma 2 9B or Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks. Gemma 2 9B is made by Google and Qwen3 VL 30B A3B 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 2 9B compare to Qwen3 VL 30B A3B Thinking in benchmarks?

Gemma 2 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

What are the context window sizes for Gemma 2 9B and Qwen3 VL 30B A3B Thinking?

Gemma 2 9B supports an unknown number of tokens and Qwen3 VL 30B A3B Thinking supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 2 9B and Qwen3 VL 30B A3B Thinking?

Key differences include multimodal support (no vs yes), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 2 9B and Qwen3 VL 30B A3B Thinking?

Gemma 2 9B is developed by Google and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.