Model Comparison
DeepSeek-V2.5 vs QvQ-72B-Preview
Comparing DeepSeek-V2.5 and QvQ-72B-Preview across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 and QvQ-72B-Preview 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-V2.5 has 162.6B more parameters than QvQ-72B-Preview, making it 221.5% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).
Input Capabilities
Supported data types and modalities
QvQ-72B-Preview supports multimodal inputs, whereas DeepSeek-V2.5 does not.
QvQ-72B-Preview can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
QvQ-72B-Preview
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while QvQ-72B-Preview uses Qwen.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Qwen
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while QvQ-72B-Preview was released on 2024-12-25.
QvQ-72B-Preview is 8 months newer than DeepSeek-V2.5.
May 8, 2024
2.0 years ago
Dec 25, 2024
1.4 years ago
7mo 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-V2.5
View detailsDeepSeek
QvQ-72B-Preview
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V2.5 vs QvQ-72B-Preview.