Model Comparison
DeepSeek VL2 vs Qwen2.5 VL 7B Instruct
Qwen2.5 VL 7B Instruct significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek VL2 outperforms in 0 benchmarks, while Qwen2.5 VL 7B Instruct is better at 8 benchmarks (ChartQA, DocVQA, InfoVQA, MMBench, MMMU, MMStar, OCRBench, TextVQA).
Qwen2.5 VL 7B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek VL2 has 18.7B more parameters than Qwen2.5 VL 7B Instruct, making it 225.7% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).
Input Capabilities
Supported data types and modalities
Both DeepSeek VL2 and Qwen2.5 VL 7B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek VL2
Qwen2.5 VL 7B Instruct
License
Usage and distribution terms
DeepSeek VL2 is licensed under deepseek, while Qwen2.5 VL 7B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek VL2 was released on 2024-12-13, while Qwen2.5 VL 7B Instruct was released on 2025-01-26.
Qwen2.5 VL 7B Instruct is 1 month newer than DeepSeek VL2.
Dec 13, 2024
1.5 years ago
Jan 26, 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
View detailsDeepSeek
Qwen2.5 VL 7B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about DeepSeek VL2 vs Qwen2.5 VL 7B Instruct.