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DeepSeek-V4.1-Flash-1017 vs Gemma 3n E2B Instructed LiteRT (Preview)

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -9.9.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to -9.9, ranking #15 overall.

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

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

Choose Gemma 3n E2B Instructed LiteRT (Preview)

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Gemma 3n E2B Instructed LiteRT (Preview)
Google
Core performance indexes
LLM Stats Score
51.0
#15
-9.9
#389
Reasoning
48.6
#18
-10.1
#382
Coding
39.1
#15
-4.5
#279
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Gemma 3n E2B Instructed LiteRT (Preview)
Math
31.8#67
-6.4#334
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 28 for Gemma 3n E2B Instructed LiteRT (Preview)

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Gemma 3n E2B Instructed LiteRT (Preview)don'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

761.3B diff

DeepSeek-V4.1-Flash-1017 has 761.3B more parameters than Gemma 3n E2B Instructed LiteRT (Preview), making it 39858.4% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Google
Gemma 3n E2B Instructed LiteRT (Preview)
1.9Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
1.9B
Gemma 3n E2B Instructed LiteRT (Preview)

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash-1017 specifies input context (1,048,576 tokens). Only DeepSeek-V4.1-Flash-1017 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Google
Gemma 3n E2B Instructed LiteRT (Preview)
Input- tokens
Output- tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Gemma 3n E2B Instructed LiteRT (Preview) support multimodal inputs.

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

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Gemma 3n E2B Instructed LiteRT (Preview)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Gemma 3n E2B 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-1017

MIT

Open weights

Gemma 3n E2B Instructed LiteRT (Preview)

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Gemma 3n E2B Instructed LiteRT (Preview) was released on 2025-05-20.

DeepSeek-V4.1-Flash-1017 is 17 months newer than Gemma 3n E2B Instructed LiteRT (Preview).

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

1.4yr newer
Gemma 3n E2B Instructed LiteRT (Preview)

May 20, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E2B Instructed LiteRT (Preview) has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V4.1-Flash-1017's cutoff date is not specified.

We can confirm Gemma 3n E2B Instructed LiteRT (Preview)'s training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash-1017's cutoff date.

DeepSeek-V4.1-Flash-1017

—

Gemma 3n E2B Instructed LiteRT (Preview)

Jun 2024

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Gemma 3n E2B Instructed LiteRT (Preview) side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Gemma 3n E2B Instructed LiteRT (Preview)
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Gemma 3n E2B Instructed LiteRT (Preview).

Which is better, DeepSeek-V4.1-Flash-1017 or Gemma 3n E2B Instructed LiteRT (Preview)?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -9.9. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Gemma 3n E2B 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-1017 compare to Gemma 3n E2B Instructed LiteRT (Preview) in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Gemma 3n E2B Instructed LiteRT (Preview) scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Gemma 3n E2B Instructed LiteRT (Preview)?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Gemma 3n E2B 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-1017 and Gemma 3n E2B Instructed LiteRT (Preview)?

Key differences include LLM Stats Score (51.0 vs -9.9), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Gemma 3n E2B Instructed LiteRT (Preview)?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Gemma 3n E2B Instructed LiteRT (Preview) is developed by Google.

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