Model Comparison

DeepSeek-V3 0324 vs Gemma 3n E2B

Comparing DeepSeek-V3 0324 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-V3 0324 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-V3 0324 has 663.0B more parameters than Gemma 3n E2B, making it 8287.5% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Google
Gemma 3n E2B
8.0Bparameters
671.0B
DeepSeek-V3 0324
8.0B
Gemma 3n E2B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Google
Gemma 3n E2B
Input- tokens
Output- tokens
Fri May 08 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B supports multimodal inputs, whereas DeepSeek-V3 0324 does not.

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

DeepSeek-V3 0324

Text
Images
Audio
Video

Gemma 3n E2B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), 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-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Gemma 3n E2B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Gemma 3n E2B was released on 2025-06-26.

Gemma 3n E2B is 3 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

Gemma 3n E2B

Jun 26, 2025

10 months ago

3mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V3 0324'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-V3 0324's cutoff date.

DeepSeek-V3 0324

—

Gemma 3n E2B

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Has open weights
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3 0324
Google
Gemma 3n E2B

FAQ

Common questions about DeepSeek-V3 0324 vs Gemma 3n E2B.

Which is better, DeepSeek-V3 0324 or Gemma 3n E2B?

DeepSeek-V3 0324 (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-V3 0324 compare to Gemma 3n E2B in benchmarks?

DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. 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-V3 0324 and Gemma 3n E2B?

DeepSeek-V3 0324 supports 164K 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-V3 0324 and Gemma 3n E2B?

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

Who makes DeepSeek-V3 0324 and Gemma 3n E2B?

DeepSeek-V3 0324 is developed by DeepSeek and Gemma 3n E2B is developed by Google.