Model Comparison

DeepSeek-V2.5 vs Gemma 3n E4B

Comparing DeepSeek-V2.5 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-V2.5 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

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 29 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Google
Gemma 3n E4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

228.0B diff

DeepSeek-V2.5 has 228.0B more parameters than Gemma 3n E4B, making it 2850.0% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Google
Gemma 3n E4B
8.0Bparameters
236.0B
DeepSeek-V2.5
8.0B
Gemma 3n E4B

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Google
Gemma 3n E4B
Input- tokens
Output- tokens
Wed Apr 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B supports multimodal inputs, whereas DeepSeek-V2.5 does not.

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

DeepSeek-V2.5

Text
Images
Audio
Video

Gemma 3n E4B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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-V2.5

deepseek

Open weights

Gemma 3n E4B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Gemma 3n E4B was released on 2025-06-26.

Gemma 3n E4B is 14 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Gemma 3n E4B

Jun 26, 2025

10 months ago

1.1yr newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V2.5'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-V2.5's cutoff date.

DeepSeek-V2.5

—

Gemma 3n E4B

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
Has open weights
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Google
Gemma 3n E4B

FAQ

Common questions about DeepSeek-V2.5 vs Gemma 3n E4B

DeepSeek-V2.5 (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.
DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%.
DeepSeek-V2.5 supports 8K 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.
Key differences include multimodal support (no vs yes), licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Gemma 3n E4B is developed by Google.