Model Comparison

DeepSeek-R1 vs Gemma 3n E2B

Comparing DeepSeek-R1 and Gemma 3n E2B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Gemma 3n E2B 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

663.0B diff

DeepSeek-R1 has 663.0B more parameters than Gemma 3n E2B, making it 8287.5% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Google
Gemma 3n E2B
8.0Bparameters
671.0B
DeepSeek-R1
8.0B
Gemma 3n E2B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3n E2B
Input- tokens
Output- tokens
Sat May 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B supports multimodal inputs, whereas DeepSeek-R1 does not.

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

DeepSeek-R1

Text
Images
Audio
Video

Gemma 3n E2B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, while Gemma 3n E2B uses a proprietary license.

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

DeepSeek-R1

MIT

Open weights

Gemma 3n E2B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Gemma 3n E2B was released on 2025-06-26.

Gemma 3n E2B is 5 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.3 years ago

Gemma 3n E2B

Jun 26, 2025

10 months ago

5mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B has a documented knowledge cutoff of 2024-06-01, while DeepSeek-R1's cutoff date is not specified.

We can confirm Gemma 3n E2B's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-R1's cutoff date.

DeepSeek-R1

—

Gemma 3n E2B

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Has open weights
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
Google
Gemma 3n E2B

FAQ

Common questions about DeepSeek-R1 vs Gemma 3n E2B.

Which is better, DeepSeek-R1 or Gemma 3n E2B?

DeepSeek-R1 (DeepSeek) and Gemma 3n E2B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-R1 compare to Gemma 3n E2B in benchmarks?

Gemma 3n E2B scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%.

What are the context window sizes for DeepSeek-R1 and Gemma 3n E2B?

DeepSeek-R1 supports 131K tokens and Gemma 3n E2B 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 DeepSeek-R1 and Gemma 3n E2B?

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

Who makes DeepSeek-R1 and Gemma 3n E2B?

DeepSeek-R1 is developed by DeepSeek and Gemma 3n E2B is developed by Google.