Model Comparison

DeepSeek-V3 0324 vs Gemma 3n E2B Instructed LiteRT (Preview)Which is better in 2026?

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Verdict: DeepSeek-V3 0324 vs Gemma 3n E2B Instructed LiteRT (Preview) — which is better?

DeepSeek-V3 0324 (by DeepSeek) and Gemma 3n E2B Instructed LiteRT (Preview) (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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

Choose DeepSeek-V3 0324 if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks

Choose Gemma 3n E2B Instructed LiteRT (Preview) if…

  • you want the most recent training data — it shipped May 2025
Want to compare interactively?Try the playground

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 LiteRT (Preview) is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Sun Jun 07 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

669.1B diff

DeepSeek-V3 0324 has 669.1B more parameters than Gemma 3n E2B Instructed LiteRT (Preview), making it 35030.9% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Google
Gemma 3n E2B Instructed LiteRT (Preview)
1.9Bparameters
671.0B
DeepSeek-V3 0324
1.9B
Gemma 3n E2B Instructed LiteRT (Preview)

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 LiteRT (Preview)
Input- tokens
Output- tokens
Sun Jun 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Gemma 3n E2B Instructed LiteRT (Preview) 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 LiteRT (Preview)

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 LiteRT (Preview) uses Gemma.

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 LiteRT (Preview)

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20.

Gemma 3n E2B Instructed LiteRT (Preview) is 2 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.2 years ago

Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

1.0 years ago

1mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed LiteRT (Preview) 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 LiteRT (Preview)'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 LiteRT (Preview)

Jun 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
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 LiteRT (Preview)

FAQ

Common questions about DeepSeek-V3 0324 vs Gemma 3n E2B Instructed LiteRT (Preview).

Which is better, DeepSeek-V3 0324 or Gemma 3n E2B Instructed LiteRT (Preview)?

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek-V3 0324 is made by DeepSeek 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.

How does DeepSeek-V3 0324 compare to Gemma 3n E2B Instructed LiteRT (Preview) 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 Instructed LiteRT (Preview) 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 Instructed LiteRT (Preview)?

DeepSeek-V3 0324 supports 164K 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.

What are the main differences between DeepSeek-V3 0324 and Gemma 3n E2B Instructed LiteRT (Preview)?

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

Who makes DeepSeek-V3 0324 and Gemma 3n E2B Instructed LiteRT (Preview)?

DeepSeek-V3 0324 is developed by DeepSeek and Gemma 3n E2B Instructed LiteRT (Preview) is developed by Google.

Related comparisons