Model Comparison

Gemma 3n E2B Instructed LiteRT (Preview) vs Qwen2.5 VL 72B Instruct

Comparing Gemma 3n E2B Instructed LiteRT (Preview) and Qwen2.5 VL 72B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 3n E2B Instructed LiteRT (Preview) and Qwen2.5 VL 72B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

70.1B diff

Qwen2.5 VL 72B Instruct has 70.1B more parameters than Gemma 3n E2B Instructed LiteRT (Preview), making it 3669.6% larger.

Google
Gemma 3n E2B Instructed LiteRT (Preview)
1.9Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
72.0Bparameters
1.9B
Gemma 3n E2B Instructed LiteRT (Preview)
72.0B
Qwen2.5 VL 72B Instruct

Input Capabilities

Supported data types and modalities

Both Gemma 3n E2B Instructed LiteRT (Preview) and Qwen2.5 VL 72B Instruct support multimodal inputs.

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

Gemma 3n E2B Instructed LiteRT (Preview)

Text
Images
Audio
Video

Qwen2.5 VL 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E2B Instructed LiteRT (Preview) is licensed under Gemma, while Qwen2.5 VL 72B Instruct uses tongyi-qianwen.

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

Gemma 3n E2B Instructed LiteRT (Preview)

Gemma

Open weights

Qwen2.5 VL 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20, while Qwen2.5 VL 72B Instruct was released on 2025-01-26.

Gemma 3n E2B Instructed LiteRT (Preview) is 4 months newer than Qwen2.5 VL 72B Instruct.

Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

1.0 years ago

3mo newer
Qwen2.5 VL 72B Instruct

Jan 26, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed LiteRT (Preview) has a documented knowledge cutoff of 2024-06-01, while Qwen2.5 VL 72B Instruct's cutoff date is not specified.

We can confirm Gemma 3n E2B Instructed LiteRT (Preview)'s training data extends to 2024-06-01, but cannot make a direct comparison without Qwen2.5 VL 72B Instruct's cutoff date.

Gemma 3n E2B Instructed LiteRT (Preview)

Jun 2024

Qwen2.5 VL 72B Instruct

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

Qwen2.5 VL 72B Instruct

View details

Alibaba Cloud / Qwen Team

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

Detailed Comparison

FAQ

Common questions about Gemma 3n E2B Instructed LiteRT (Preview) vs Qwen2.5 VL 72B Instruct.

Which is better, Gemma 3n E2B Instructed LiteRT (Preview) or Qwen2.5 VL 72B Instruct?

Gemma 3n E2B Instructed LiteRT (Preview) (Google) and Qwen2.5 VL 72B Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemma 3n E2B Instructed LiteRT (Preview) compare to Qwen2.5 VL 72B Instruct in benchmarks?

Gemma 3n E2B Instructed LiteRT (Preview) scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%. Qwen2.5 VL 72B Instruct scores DocVQA: 96.4%, Android Control Low_EM: 93.7%, ChartQA: 89.5%, OCRBench: 88.5%, AI2D: 88.4%.

What are the main differences between Gemma 3n E2B Instructed LiteRT (Preview) and Qwen2.5 VL 72B Instruct?

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

Who makes Gemma 3n E2B Instructed LiteRT (Preview) and Qwen2.5 VL 72B Instruct?

Gemma 3n E2B Instructed LiteRT (Preview) is developed by Google and Qwen2.5 VL 72B Instruct is developed by Alibaba Cloud / Qwen Team.