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Gemma 2 27B vs Qwen3 VL 8B Thinking

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

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.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Gemma 2 27B

  • you are already invested in the Google ecosystem

Choose Qwen3 VL 8B Thinking

  • 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

At a glance

The differences that matter most.

Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.18 / M
Output price
— / M
$2.09 / M
Context window
262,144
Released
Jun 2024
Sep 2025
License
Gemma
Apache 2.0

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.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

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
Tue Aug 25 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

2.2 years ago

Qwen3 VL 8B Thinking

Sep 22, 2025

11 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

Judge for yourself.

Run your own prompts against Gemma 2 27B and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.

Gemma 2 27B
✓ Preferred
Qwen3 VL 8B Thinking
Open in Playground

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.