DeepSeek-V4.1-Flash-1017 vs DeepSeek VL2 Small
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 0.9.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 0.9, 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 — it leads those capability indexes
- you want the most recent training data — it shipped Oct 2026
Choose DeepSeek VL2 Small
- you are already invested in the DeepSeek ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 14 for DeepSeek VL2 Small
DeepSeek-V4.1-Flash-1017 and DeepSeek VL2 Smalldon'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
DeepSeek-V4.1-Flash-1017 has 747.2B more parameters than DeepSeek VL2 Small, making it 4670.0% larger.
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).
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and DeepSeek VL2 Small support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
DeepSeek VL2 Small
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 is licensed under MIT, while DeepSeek VL2 Small uses deepseek.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
deepseek
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while DeepSeek VL2 Small was released on 2024-12-13.
DeepSeek-V4.1-Flash-1017 is 22 months newer than DeepSeek VL2 Small.
Oct 17, 2026
3 days ago
1.8yr newerDec 13, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and DeepSeek VL2 Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs DeepSeek VL2 Small.
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