Model Comparison
DeepSeek VL2 Small vs DeepSeek-R1
Comparing DeepSeek VL2 Small and DeepSeek-R1 across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek VL2 Small and DeepSeek-R1 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek-R1 has 655.0B more parameters than DeepSeek VL2 Small, making it 4093.8% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
DeepSeek VL2 Small supports multimodal inputs, whereas DeepSeek-R1 does not.
DeepSeek VL2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek VL2 Small
DeepSeek-R1
License
Usage and distribution terms
DeepSeek VL2 Small is licensed under deepseek, while DeepSeek-R1 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek VL2 Small was released on 2024-12-13, while DeepSeek-R1 was released on 2025-01-20.
DeepSeek-R1 is 1 month newer than DeepSeek VL2 Small.
Dec 13, 2024
1.4 years ago
Jan 20, 2025
1.3 years ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek VL2 Small
View detailsDeepSeek
DeepSeek-R1
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek VL2 Small vs DeepSeek-R1.