Model Comparison
DeepSeek VL2 vs o1
o1 significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek VL2 outperforms in 0 benchmarks, while o1 is better at 2 benchmarks (MathVista, MMMU).
o1 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Context Window
Maximum input and output token capacity
o1 accepts 200,000 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while o1 is limited to 100,000 tokens.
Input Capabilities
Supported data types and modalities
DeepSeek VL2 supports multimodal inputs, whereas o1 does not.
DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek VL2
o1
License
Usage and distribution terms
DeepSeek VL2 is licensed under deepseek, while o1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek VL2 was released on 2024-12-13, while o1 was released on 2024-12-17.
o1 is 0 month newer than DeepSeek VL2.
Dec 13, 2024
1.4 years ago
Dec 17, 2024
1.4 years ago
4d newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek VL2 is available from Replicate. o1 is available from Azure, OpenAI.
DeepSeek VL2
o1
Outputs Comparison
Key Takeaways
DeepSeek VL2
View detailsDeepSeek
o1
View detailsOpenAI
Detailed Comparison
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FAQ
Common questions about DeepSeek VL2 vs o1.