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DeepSeek-V4.1-Flash-1017 vs DiffusionGemma 26B-A4B

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 19.0.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 19.0, ranking #15 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 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-1017

  • overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and agents — 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 Oct 2026

Choose DiffusionGemma 26B-A4B

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
DiffusionGemma 26B-A4B
Google
Core performance indexes
LLM Stats Score
51.2
#15
19.0
#230
Reasoning
48.8
#18
18.7
#228
Agents
38.7
#8
0.4
#197
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
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

3 shared
Index
DeepSeek-V4.1-Flash-1017
DiffusionGemma 26B-A4B
Math
31.8#69
17.5#203
Vision
32.3#25
10.4#137
Multimodal
35.0#14
14.6#111
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 14 for DiffusionGemma 26B-A4B

1 shared

DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (Humanity's Last Exam), while DiffusionGemma 26B-A4B is better at 0 benchmarks.

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Mon Oct 26 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

738.0B diff

DeepSeek-V4.1-Flash-1017 has 738.0B more parameters than DiffusionGemma 26B-A4B, making it 2928.6% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Google
DiffusionGemma 26B-A4B
25.2Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
25.2B
DiffusionGemma 26B-A4B

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
DiffusionGemma 26B-A4B
Input- tokens
Output- tokens
Mon Oct 26 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and DiffusionGemma 26B-A4B 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

DiffusionGemma 26B-A4B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while DiffusionGemma 26B-A4B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

DiffusionGemma 26B-A4B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while DiffusionGemma 26B-A4B was released on 2026-06-10.

DeepSeek-V4.1-Flash-1017 is 4 months newer than DiffusionGemma 26B-A4B.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

1 weeks ago

4mo newer
DiffusionGemma 26B-A4B

Jun 10, 2026

4 months ago

Knowledge Cutoff

When training data ends

DiffusionGemma 26B-A4B has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V4.1-Flash-1017's cutoff date is not specified.

We can confirm DiffusionGemma 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash-1017's cutoff date.

DeepSeek-V4.1-Flash-1017

—

DiffusionGemma 26B-A4B

Jan 2025

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and DiffusionGemma 26B-A4B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
DiffusionGemma 26B-A4B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs DiffusionGemma 26B-A4B.

Which is better, DeepSeek-V4.1-Flash-1017 or DiffusionGemma 26B-A4B?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 19.0. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and DiffusionGemma 26B-A4B 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 DiffusionGemma 26B-A4B 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%. DiffusionGemma 26B-A4B scores MMMLU: 81.5%, MMLU-Pro: 77.6%, GPQA: 73.2%, MathVision: 70.5%, AIME 2026: 69.1%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and DiffusionGemma 26B-A4B?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and DiffusionGemma 26B-A4B 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 DiffusionGemma 26B-A4B?

Key differences include LLM Stats Score (51.2 vs 19.0), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and DiffusionGemma 26B-A4B?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and DiffusionGemma 26B-A4B is developed by Google.

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