The AI arena is free today

Open Superagent

Gemma 2 27B vs QvQ-72B-Preview

QvQ-72B-Preview leads the LLM Stats Score 8.1 to -0.5.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

QvQ-72B-Preview leads the overall LLM Stats Score 8.1 to -0.5, ranking #271 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemma 2 27B

  • you are already invested in the Google ecosystem

Choose QvQ-72B-Preview

  • overall performance matters — it scores 8.1 and ranks #271 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Dec 2024

At a glance

The differences that matter most.

Core performance indexes
-0.5
#317
8.1
#271
-0.9
#313
8.4
#263
Cost, coverage & limits
Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemma 2 27B
QvQ-72B-Preview
-0.3#288
9.8#244
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for Gemma 2 27B · 4 for QvQ-72B-Preview

No common benchmarks found

Gemma 2 27B and QvQ-72B-Previewdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

46.2B diff

QvQ-72B-Preview has 46.2B more parameters than Gemma 2 27B, making it 169.9% larger.

Google
Gemma 2 27B
27.2Bparameters
Alibaba Cloud / Qwen Team
QvQ-72B-Preview
73.4Bparameters
27.2B
Gemma 2 27B
73.4B
QvQ-72B-Preview

Input capabilities

Documented input modalities across available providers

QvQ-72B-Preview supports multimodal inputs, whereas Gemma 2 27B does not.

QvQ-72B-Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 27B

Text
Images
Audio
Video

QvQ-72B-Preview

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 27B is licensed under Gemma, while QvQ-72B-Preview uses Qwen.

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

Gemma 2 27B

Gemma

Open weights

QvQ-72B-Preview

Qwen

Open weights

Release Timeline

When each model was launched

Gemma 2 27B was released on 2024-06-27, while QvQ-72B-Preview was released on 2024-12-25.

QvQ-72B-Preview is 6 months newer than Gemma 2 27B.

Gemma 2 27B

Jun 27, 2024

2.2 years ago

QvQ-72B-Preview

Dec 25, 2024

1.7 years 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

Judge for yourself.

Run your own prompts against Gemma 2 27B and QvQ-72B-Preview side-by-side, then vote on the output you prefer.

Gemma 2 27B
✓ Preferred
QvQ-72B-Preview
Open in Playground

FAQ

Common questions about Gemma 2 27B vs QvQ-72B-Preview.

Which is better, Gemma 2 27B or QvQ-72B-Preview?

QvQ-72B-Preview leads the LLM Stats Score 8.1 to -0.5. Gemma 2 27B is made by Google and QvQ-72B-Preview is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemma 2 27B compare to QvQ-72B-Preview in benchmarks?

Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%. QvQ-72B-Preview scores MathVista: 71.4%, MMMU: 70.3%, MathVision: 35.9%, OlympiadBench: 20.4%.

What are the main differences between Gemma 2 27B and QvQ-72B-Preview?

Key differences include LLM Stats Score (-0.5 vs 8.1), multimodal support (no vs yes), licensing (Gemma vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 2 27B and QvQ-72B-Preview?

Gemma 2 27B is developed by Google and QvQ-72B-Preview is developed by Alibaba Cloud / Qwen Team.