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DeepSeek-V4.1-Flash-1017 vs DeepSeek VL2

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 2.6.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 2.6, ranking #15 overall.

DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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 — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose DeepSeek VL2

  • you are already invested in the DeepSeek ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
DeepSeek VL2
DeepSeek
Core performance indexes
LLM Stats Score
51.0
#15
2.6
#335
Reasoning
48.6
#18
-2.1
#353
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
129,280

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
DeepSeek VL2
Vision
32.2#26
2.0#186
Multimodal
35.0#14
5.0#156
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 14 for DeepSeek VL2

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and DeepSeek VL2don'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

736.2B diff

DeepSeek-V4.1-Flash-1017 has 736.2B more parameters than DeepSeek VL2, making it 2726.7% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
DeepSeek
DeepSeek VL2
27.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
27.0B
DeepSeek VL2

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and DeepSeek VL2 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

DeepSeek VL2

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while DeepSeek VL2 uses deepseek.

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

DeepSeek-V4.1-Flash-1017

MIT

Open weights

DeepSeek VL2

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while DeepSeek VL2 was released on 2024-12-13.

DeepSeek-V4.1-Flash-1017 is 22 months newer than DeepSeek VL2.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

1.8yr newer
DeepSeek VL2

Dec 13, 2024

1.8 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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. DeepSeek VL2 is available from Replicate.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

DeepSeek VL2

replicate logo
Replicate
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and DeepSeek VL2 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
DeepSeek VL2
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs DeepSeek VL2.

Which is better, DeepSeek-V4.1-Flash-1017 or DeepSeek VL2?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 2.6. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and DeepSeek VL2 is made by DeepSeek. 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 DeepSeek VL2 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%. DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and DeepSeek VL2?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and DeepSeek VL2 supports 129K 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 DeepSeek VL2?

Key differences include LLM Stats Score (51.0 vs 2.6), context window (1.0M vs 129K), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

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