Model Comparison

DeepSeek-V3 0324 vs Gemma 3n E2B Instructed

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3 0324 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3n E2B Instructed is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Fri Apr 17 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
Fri Apr 17 2026 • llm-stats.com
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
Google
Gemma 3n E2B Instructed
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

663.0B diff

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

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

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 Instructed
Input- tokens
Output- tokens
Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Gemma 3n E2B Instructed 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 Instructed

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 Instructed 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 Instructed

Proprietary

Closed source

Release Timeline

When each model was launched

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

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

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

Gemma 3n E2B Instructed

Jun 26, 2025

9 months ago

3mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed 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 Instructed'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 Instructed

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Has open weights
Higher GPQA score (68.4% vs 24.8%)
Higher LiveCodeBench score (49.2% vs 13.2%)
Higher MMLU-Pro score (81.2% vs 40.5%)
Google
Supports multimodal inputs

Detailed Comparison

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

FAQ

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

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek-V3 0324 is made by DeepSeek and Gemma 3n E2B Instructed is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
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 Instructed scores HumanEval: 66.5%, MMLU: 60.1%, Global-MMLU-Lite: 59.0%, MBPP: 56.6%, Global-MMLU: 55.1%.
DeepSeek-V3 0324 supports 164K tokens and Gemma 3n E2B Instructed 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 multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 0324 is developed by DeepSeek and Gemma 3n E2B Instructed is developed by Google.