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DeepSeek-V3.2-Exp vs Gemma 3n E4B

DeepSeek-V3.2-Exp leads the LLM Stats Score 28.2 to -6.2.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V3.2-Exp leads the overall LLM Stats Score 28.2 to -6.2, ranking #140 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2-Exp

  • overall performance matters — it scores 28.2 and ranks #140 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune

Choose Gemma 3n E4B

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V3.2-Exp
DeepSeek
Gemma 3n E4B
Google
Core performance indexes
LLM Stats Score
28.2
#140
-6.2
#367
Reasoning
28.1
#136
-6.4
#359
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.27 / M
— / M
Output price
$0.41 / M
— / M
Context window
163,840
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2-Exp
Gemma 3n E4B
Math
26.3#104
-2.8#313
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2-Exp · 11 for Gemma 3n E4B

No common benchmarks found

DeepSeek-V3.2-Exp and Gemma 3n E4Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

677.0B diff

DeepSeek-V3.2-Exp has 677.0B more parameters than Gemma 3n E4B, making it 8462.5% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Google
Gemma 3n E4B
8.0Bparameters
685.0B
DeepSeek-V3.2-Exp
8.0B
Gemma 3n E4B

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Google
Gemma 3n E4B
Input- tokens
Output- tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemma 3n E4B supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

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

DeepSeek-V3.2-Exp

Text
Images
Audio
Video

Gemma 3n E4B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, 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-V3.2-Exp

MIT

Open weights

Gemma 3n E4B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Gemma 3n E4B was released on 2025-06-26.

DeepSeek-V3.2-Exp is 3 months newer than Gemma 3n E4B.

DeepSeek-V3.2-Exp

Sep 29, 2025

11 months ago

3mo newer
Gemma 3n E4B

Jun 26, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V3.2-Exp'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-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

—

Gemma 3n E4B

Jun 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Exp and Gemma 3n E4B side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Exp
✓ Preferred
Gemma 3n E4B
Open in Playground

FAQ

Common questions about DeepSeek-V3.2-Exp vs Gemma 3n E4B.

Which is better, DeepSeek-V3.2-Exp or Gemma 3n E4B?

DeepSeek-V3.2-Exp leads the LLM Stats Score 28.2 to -6.2. DeepSeek-V3.2-Exp is made by DeepSeek and Gemma 3n E4B is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2-Exp compare to Gemma 3n E4B in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%.

What are the context window sizes for DeepSeek-V3.2-Exp and Gemma 3n E4B?

DeepSeek-V3.2-Exp supports 164K 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.

What are the main differences between DeepSeek-V3.2-Exp and Gemma 3n E4B?

Key differences include LLM Stats Score (28.2 vs -6.2), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Exp and Gemma 3n E4B?

DeepSeek-V3.2-Exp is developed by DeepSeek and Gemma 3n E4B is developed by Google.

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