Model Comparison

DeepSeek-R1-0528 vs Gemma 3n E4B

Comparing DeepSeek-R1-0528 and Gemma 3n E4B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1-0528 and Gemma 3n E4B 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-R1-0528 has 663.0B more parameters than Gemma 3n E4B, making it 8287.5% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Google
Gemma 3n E4B
8.0Bparameters
671.0B
DeepSeek-R1-0528
8.0B
Gemma 3n E4B

Context Window

Maximum input and output token capacity

Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3n E4B
Input- tokens
Output- tokens
Sun May 31 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B supports multimodal inputs, whereas DeepSeek-R1-0528 does not.

Gemma 3n E4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1-0528

Text
Images
Audio
Video

Gemma 3n E4B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Gemma 3n E4B uses a proprietary license.

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

DeepSeek-R1-0528

MIT

Open weights

Gemma 3n E4B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Gemma 3n E4B was released on 2025-06-26.

Gemma 3n E4B is 1 month newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

1.0 years ago

Gemma 3n E4B

Jun 26, 2025

11 months ago

4w newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while DeepSeek-R1-0528's cutoff date is not specified.

We can confirm Gemma 3n E4B's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.

DeepSeek-R1-0528

—

Gemma 3n E4B

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-R1-0528
Google
Gemma 3n E4B

FAQ

Common questions about DeepSeek-R1-0528 vs Gemma 3n E4B.

Which is better, DeepSeek-R1-0528 or Gemma 3n E4B?

DeepSeek-R1-0528 (DeepSeek) and Gemma 3n E4B (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-R1-0528 compare to Gemma 3n E4B in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%.

What are the context window sizes for DeepSeek-R1-0528 and Gemma 3n E4B?

DeepSeek-R1-0528 supports 131K tokens and Gemma 3n E4B 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-R1-0528 and Gemma 3n E4B?

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-R1-0528 and Gemma 3n E4B?

DeepSeek-R1-0528 is developed by DeepSeek and Gemma 3n E4B is developed by Google.