The AI arena is free today

Open Superagent

DeepSeek-V4.1-Flash vs Gemma 3n E4B

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -6.2.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to -6.2, ranking #13 overall.

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

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026
  • 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-V4.1-Flash
DeepSeek
Gemma 3n E4B
Google
Core performance indexes
LLM Stats Score
51.8
#13
-6.2
#361
Reasoning
48.9
#18
-6.4
#353
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
Gemma 3n E4B
Math
35.2#43
-2.8#312
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 11 for Gemma 3n E4B

No common benchmarks found

DeepSeek-V4.1-Flash 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

755.2B diff

DeepSeek-V4.1-Flash has 755.2B more parameters than Gemma 3n E4B, making it 9440.1% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Google
Gemma 3n E4B
8.0Bparameters
763.2B
DeepSeek-V4.1-Flash
8.0B
Gemma 3n E4B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Google
Gemma 3n E4B
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Gemma 3n E4B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Gemma 3n E4B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash 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-V4.1-Flash

MIT

Open weights

Gemma 3n E4B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Gemma 3n E4B was released on 2025-06-26.

DeepSeek-V4.1-Flash is 15 months newer than Gemma 3n E4B.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

1.2yr 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-V4.1-Flash'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-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

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-V4.1-Flash and Gemma 3n E4B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Gemma 3n E4B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Gemma 3n E4B.

Which is better, DeepSeek-V4.1-Flash or Gemma 3n E4B?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -6.2. DeepSeek-V4.1-Flash 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-V4.1-Flash compare to Gemma 3n E4B in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. 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-V4.1-Flash and Gemma 3n E4B?

DeepSeek-V4.1-Flash supports 1.0M 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-V4.1-Flash and Gemma 3n E4B?

Key differences include LLM Stats Score (51.8 vs -6.2), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Gemma 3n E4B?

DeepSeek-V4.1-Flash is developed by DeepSeek and Gemma 3n E4B is developed by Google.

Related comparisons