Model Comparison

Gemma 2 27B vs Qwen3 VL 8B ThinkingWhich is better in 2026?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Verdict: Gemma 2 27B vs Qwen3 VL 8B Thinking — which is better?

Gemma 2 27B (by Google) and Qwen3 VL 8B 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 27B outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 1 benchmark (MMLU). Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Choose Gemma 2 27B if…

  • you are already invested in the Google ecosystem

Choose Qwen3 VL 8B 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 27B outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 1 benchmark (MMLU).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Sat Jun 06 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

18.2B diff

Gemma 2 27B has 18.2B more parameters than Qwen3 VL 8B Thinking, making it 202.2% larger.

Google
Gemma 2 27B
27.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
9.0Bparameters
27.2B
Gemma 2 27B
9.0B
Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 8B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 8B Thinking specifies output context (262,144 tokens).

Google
Gemma 2 27B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
Input262,144 tokens
Output262,144 tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 8B Thinking supports multimodal inputs, whereas Gemma 2 27B does not.

Qwen3 VL 8B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 27B

Text
Images
Audio
Video

Qwen3 VL 8B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 27B is licensed under Gemma, while Qwen3 VL 8B Thinking uses Apache 2.0.

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

Gemma 2 27B

Gemma

Open weights

Qwen3 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 2 27B was released on 2024-06-27, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 15 months newer than Gemma 2 27B.

Gemma 2 27B

Jun 27, 2024

1.9 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

8 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 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs
Higher MMLU score (85.2% vs 75.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 27B
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking

FAQ

Common questions about Gemma 2 27B vs Qwen3 VL 8B Thinking.

Which is better, Gemma 2 27B or Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Gemma 2 27B is made by Google and Qwen3 VL 8B 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 27B compare to Qwen3 VL 8B Thinking in benchmarks?

Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

What are the context window sizes for Gemma 2 27B and Qwen3 VL 8B Thinking?

Gemma 2 27B supports an unknown number of tokens and Qwen3 VL 8B Thinking supports 262K 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 27B and Qwen3 VL 8B 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 27B and Qwen3 VL 8B Thinking?

Gemma 2 27B is developed by Google and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.