Model Comparison

Gemini 1.0 Pro vs Gemma 3n E2B Instructed LiteRT (Preview)

Gemini 1.0 Pro significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 1.0 Pro outperforms in 2 benchmarks (GPQA, MMLU), while Gemma 3n E2B Instructed LiteRT (Preview) is better at 0 benchmarks.

Gemini 1.0 Pro significantly outperforms across most benchmarks.

Sat May 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.0 Pro specifies input context (32,760 tokens). Only Gemini 1.0 Pro specifies output context (8,192 tokens).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Google
Gemma 3n E2B Instructed LiteRT (Preview)
Input- tokens
Output- tokens
Sat May 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B Instructed LiteRT (Preview) supports multimodal inputs, whereas Gemini 1.0 Pro does not.

Gemma 3n E2B Instructed LiteRT (Preview) can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.0 Pro

Text
Images
Audio
Video

Gemma 3n E2B Instructed LiteRT (Preview)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Gemma 3n E2B Instructed LiteRT (Preview) uses Gemma.

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

Gemini 1.0 Pro

Proprietary

Closed source

Gemma 3n E2B Instructed LiteRT (Preview)

Gemma

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20.

Gemma 3n E2B Instructed LiteRT (Preview) is 15 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.2 years ago

Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

11 months ago

1.3yr newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a knowledge cutoff of 2024-02-01, while Gemma 3n E2B Instructed LiteRT (Preview) has a cutoff of 2024-06-01.

Gemma 3n E2B Instructed LiteRT (Preview) has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to Gemini 1.0 Pro (2024-02-01).

Gemini 1.0 Pro

Feb 2024

Gemma 3n E2B Instructed LiteRT (Preview)

Jun 2024

4 mo newer

Outputs Comparison

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Key Takeaways

Google
Larger context window (32,760 tokens)
Higher GPQA score (27.9% vs 24.8%)
Higher MMLU score (71.8% vs 60.1%)
Google
Supports multimodal inputs
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Google
Gemma 3n E2B Instructed LiteRT (Preview)

FAQ

Common questions about Gemini 1.0 Pro vs Gemma 3n E2B Instructed LiteRT (Preview).

Which is better, Gemini 1.0 Pro or Gemma 3n E2B Instructed LiteRT (Preview)?

Gemini 1.0 Pro significantly outperforms across most benchmarks. Gemini 1.0 Pro is made by Google and Gemma 3n E2B Instructed LiteRT (Preview) is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 1.0 Pro compare to Gemma 3n E2B Instructed LiteRT (Preview) in benchmarks?

Gemini 1.0 Pro scores BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%, MMMU: 47.9%. Gemma 3n E2B Instructed LiteRT (Preview) scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%.

What are the context window sizes for Gemini 1.0 Pro and Gemma 3n E2B Instructed LiteRT (Preview)?

Gemini 1.0 Pro supports 33K tokens and Gemma 3n E2B Instructed LiteRT (Preview) supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.0 Pro and Gemma 3n E2B Instructed LiteRT (Preview)?

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