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DeepSeek-V4.1-Flash vs Gemma 2 27B

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -0.7.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to -0.7, ranking #12 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 #12 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Gemma 2 27B

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Gemma 2 27B
Google
Core performance indexes
LLM Stats Score
51.8
#12
-0.7
#329
Reasoning
48.9
#17
-1.1
#325
Coding
44.4
#5
-7.9
#262
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 2 27B
Math
35.2#43
-0.7#297
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 16 for Gemma 2 27B

No common benchmarks found

DeepSeek-V4.1-Flash and Gemma 2 27Bdon'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

736.0B diff

DeepSeek-V4.1-Flash has 736.0B more parameters than Gemma 2 27B, making it 2705.9% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Google
Gemma 2 27B
27.2Bparameters
763.2B
DeepSeek-V4.1-Flash
27.2B
Gemma 2 27B

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 2 27B
Input- tokens
Output- tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas Gemma 2 27B does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Gemma 2 27B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Gemma 2 27B 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 2 27B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Gemma 2 27B was released on 2024-06-27.

DeepSeek-V4.1-Flash is 27 months newer than Gemma 2 27B.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 days ago

2.2yr newer
Gemma 2 27B

Jun 27, 2024

2.2 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

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 2 27B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Gemma 2 27B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Gemma 2 27B.

Which is better, DeepSeek-V4.1-Flash or Gemma 2 27B?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -0.7. DeepSeek-V4.1-Flash is made by DeepSeek and Gemma 2 27B 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 2 27B 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 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%.

What are the context window sizes for DeepSeek-V4.1-Flash and Gemma 2 27B?

DeepSeek-V4.1-Flash supports 1.0M tokens and Gemma 2 27B 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 2 27B?

Key differences include LLM Stats Score (51.8 vs -0.7), multimodal support (yes vs no), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Gemma 2 27B?

DeepSeek-V4.1-Flash is developed by DeepSeek and Gemma 2 27B is developed by Google.

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