Model Comparison
o1 vs DeepSeek VL2 Tiny
o1 significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
o1 outperforms in 2 benchmarks (MathVista, MMMU), while DeepSeek VL2 Tiny is better at 0 benchmarks.
o1 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Context Window
Maximum input and output token capacity
Only o1 specifies input context (200,000 tokens). Only o1 specifies output context (100,000 tokens).
Input Capabilities
Supported data types and modalities
DeepSeek VL2 Tiny supports multimodal inputs, whereas o1 does not.
DeepSeek VL2 Tiny can handle both text and other forms of data like images, making it suitable for multimodal applications.
o1
DeepSeek VL2 Tiny
License
Usage and distribution terms
o1 is licensed under a proprietary license, while DeepSeek VL2 Tiny uses deepseek.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
deepseek
Open weights
Release Timeline
When each model was launched
o1 was released on 2024-12-17, while DeepSeek VL2 Tiny was released on 2024-12-13.
o1 is 0 month newer than DeepSeek VL2 Tiny.
Dec 17, 2024
1.4 years ago
4d newerDec 13, 2024
1.4 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
Key Takeaways
o1
View detailsOpenAI
DeepSeek VL2 Tiny
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about o1 vs DeepSeek VL2 Tiny.