The AI arena is free today

Open Superagent

DeepSeek-V4.1-Flash vs Gemma 3n E4B Instructed LiteRT Preview

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -5.2.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to -5.2, ranking #13 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.

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 and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose Gemma 3n E4B Instructed LiteRT Preview

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

Core performance indexes
51.8
#13
-5.2
#356
48.9
#18
-5.9
#351
44.2
#5
-0.1
#241
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
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 Instructed LiteRT Preview
35.2#43
-1.3#302
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 28 for Gemma 3n E4B Instructed LiteRT Preview

1 shared

DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Gemma 3n E4B Instructed LiteRT Preview is better at 0 benchmarks.

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

761.3B diff

DeepSeek-V4.1-Flash has 761.3B more parameters than Gemma 3n E4B Instructed LiteRT Preview, making it 39858.4% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Google
Gemma 3n E4B Instructed LiteRT Preview
1.9Bparameters
763.2B
DeepSeek-V4.1-Flash
1.9B
Gemma 3n E4B Instructed LiteRT Preview

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 Instructed LiteRT Preview
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 Instructed LiteRT Preview 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 Instructed LiteRT Preview

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Gemma 3n E4B Instructed LiteRT Preview uses Gemma.

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 Instructed LiteRT Preview

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Gemma 3n E4B Instructed LiteRT Preview was released on 2025-05-20.

DeepSeek-V4.1-Flash is 16 months newer than Gemma 3n E4B Instructed LiteRT Preview.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

1.3yr newer
Gemma 3n E4B Instructed LiteRT Preview

May 20, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed LiteRT Preview 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 Instructed LiteRT Preview'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 Instructed LiteRT Preview

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 Instructed LiteRT Preview side-by-side, then vote on the output you prefer.

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

FAQ

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

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

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -5.2. DeepSeek-V4.1-Flash is made by DeepSeek and Gemma 3n E4B Instructed LiteRT Preview 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 Instructed LiteRT Preview 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 Instructed LiteRT Preview scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, HumanEval: 75.0%.

What are the context window sizes for DeepSeek-V4.1-Flash and Gemma 3n E4B Instructed LiteRT Preview?

DeepSeek-V4.1-Flash supports 1.0M tokens and Gemma 3n E4B 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-V4.1-Flash and Gemma 3n E4B Instructed LiteRT Preview?

Key differences include LLM Stats Score (51.8 vs -5.2), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.

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

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