Model Comparison

DeepSeek-V3.1 vs Gemma 3n E2B InstructedWhich is better in 2026?

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Verdict: DeepSeek-V3.1 vs Gemma 3n E2B Instructed — which is better?

DeepSeek-V3.1 (by DeepSeek) and Gemma 3n E2B Instructed (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-V3.1 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3n E2B Instructed is better at 0 benchmarks. DeepSeek-V3.1 significantly outperforms across most benchmarks.

Choose DeepSeek-V3.1 if…

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
  • you need open weights you can self-host or fine-tune

Choose Gemma 3n E2B Instructed if…

  • you want the most recent training data — it shipped Jun 2025

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3.1 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3n E2B Instructed is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

663.0B diff

DeepSeek-V3.1 has 663.0B more parameters than Gemma 3n E2B Instructed, making it 8287.5% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Google
Gemma 3n E2B Instructed
8.0Bparameters
671.0B
DeepSeek-V3.1
8.0B
Gemma 3n E2B Instructed

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.1 specifies input context (163,840 tokens). Only DeepSeek-V3.1 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Google
Gemma 3n E2B Instructed
Input- tokens
Output- tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B Instructed supports multimodal inputs, whereas DeepSeek-V3.1 does not.

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

DeepSeek-V3.1

Text
Images
Audio
Video

Gemma 3n E2B Instructed

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, 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-V3.1

MIT

Open weights

Gemma 3n E2B Instructed

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Gemma 3n E2B Instructed was released on 2025-06-26.

Gemma 3n E2B Instructed is 6 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.5 years ago

Gemma 3n E2B Instructed

Jun 26, 2025

1.1 years ago

5mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V3.1'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-V3.1's cutoff date.

DeepSeek-V3.1

—

Gemma 3n E2B Instructed

Jun 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (163,840 tokens)
Has open weights
Higher AIME 2025 score (49.8% vs 6.7%)
Higher GPQA score (74.9% vs 24.8%)
Higher LiveCodeBench score (56.4% vs 13.2%)
Higher MMLU-Pro score (83.7% vs 40.5%)
Google
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.1 and Gemma 3n E2B Instructed side-by-side, then vote on the output you prefer.

DeepSeek-V3.1
✓ Preferred
Gemma 3n E2B Instructed
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Google
Gemma 3n E2B Instructed

FAQ

Common questions about DeepSeek-V3.1 vs Gemma 3n E2B Instructed.

Which is better, DeepSeek-V3.1 or Gemma 3n E2B Instructed?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 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.

How does DeepSeek-V3.1 compare to Gemma 3n E2B Instructed in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Gemma 3n E2B Instructed scores HumanEval: 66.5%, MMLU: 60.1%, Global-MMLU-Lite: 59.0%, MBPP: 56.6%, Global-MMLU: 55.1%.

What are the context window sizes for DeepSeek-V3.1 and Gemma 3n E2B Instructed?

DeepSeek-V3.1 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.

What are the main differences between DeepSeek-V3.1 and Gemma 3n E2B Instructed?

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-V3.1 and Gemma 3n E2B Instructed?

DeepSeek-V3.1 is developed by DeepSeek and Gemma 3n E2B Instructed is developed by Google.

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