Model Comparison

Gemini 2.5 Flash-Lite vs Gemma 3n E2B Instructed LiteRT (Preview)

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemini 2.5 Flash-Lite outperforms in 4 benchmarks (AIME 2025, Global-MMLU-Lite, GPQA, LiveCodeBench), while Gemma 3n E2B Instructed LiteRT (Preview) is better at 0 benchmarks.

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks.

Sun Apr 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sun Apr 19 2026 • llm-stats.com
Google
Gemini 2.5 Flash-Lite
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Google
Gemma 3n E2B Instructed LiteRT (Preview)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Gemini 2.5 Flash-Lite specifies input context (1,048,576 tokens). Only Gemini 2.5 Flash-Lite specifies output context (65,536 tokens).

Google
Gemini 2.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Google
Gemma 3n E2B Instructed LiteRT (Preview)
Input- tokens
Output- tokens
Sun Apr 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 2.5 Flash-Lite and Gemma 3n E2B Instructed LiteRT (Preview) support multimodal inputs.

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

Gemini 2.5 Flash-Lite

Text
Images
Audio
Video

Gemma 3n E2B Instructed LiteRT (Preview)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.5 Flash-Lite is licensed under Creative Commons Attribution 4.0 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 2.5 Flash-Lite

Creative Commons Attribution 4.0 License

Open weights

Gemma 3n E2B Instructed LiteRT (Preview)

Gemma

Open weights

Release Timeline

When each model was launched

Gemini 2.5 Flash-Lite was released on 2025-06-17, while Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20.

Gemini 2.5 Flash-Lite is 1 month newer than Gemma 3n E2B Instructed LiteRT (Preview).

Gemini 2.5 Flash-Lite

Jun 17, 2025

10 months ago

4w newer
Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

11 months ago

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash-Lite has a knowledge cutoff of 2025-01-01, while Gemma 3n E2B Instructed LiteRT (Preview) has a cutoff of 2024-06-01.

Gemini 2.5 Flash-Lite has more recent training data (up to 2025-01-01), making it potentially better informed about events through that date compared to Gemma 3n E2B Instructed LiteRT (Preview) (2024-06-01).

Gemini 2.5 Flash-Lite

Jan 2025

7 mo newer
Gemma 3n E2B Instructed LiteRT (Preview)

Jun 2024

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Higher AIME 2025 score (49.8% vs 6.7%)
Higher Global-MMLU-Lite score (81.1% vs 59.0%)
Higher GPQA score (64.6% vs 24.8%)
Higher LiveCodeBench score (33.7% vs 13.2%)
Google

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 2.5 Flash-Lite
Google
Gemma 3n E2B Instructed LiteRT (Preview)

FAQ

Common questions about Gemini 2.5 Flash-Lite vs Gemma 3n E2B Instructed LiteRT (Preview)

Gemini 2.5 Flash-Lite significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite 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.
Gemini 2.5 Flash-Lite scores FACTS Grounding: 84.1%, Global-MMLU-Lite: 81.1%, MMMU: 72.9%, GPQA: 64.6%, Vibe-Eval: 51.3%. Gemma 3n E2B Instructed LiteRT (Preview) scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%.
Gemini 2.5 Flash-Lite supports 1.0M 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.
Key differences include licensing (Creative Commons Attribution 4.0 License vs Gemma). See the full comparison above for benchmark-by-benchmark results.