Model Comparison
DeepSeek-V2.5 vs Qwen3 VL 32B Instruct
Qwen3 VL 32B Instruct significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 0 benchmarks, while Qwen3 VL 32B Instruct is better at 1 benchmark (MMLU).
Qwen3 VL 32B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek-V2.5 has 203.0B more parameters than Qwen3 VL 32B Instruct, making it 615.2% 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
Qwen3 VL 32B Instruct supports multimodal inputs, whereas DeepSeek-V2.5 does not.
Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
Qwen3 VL 32B Instruct
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Qwen3 VL 32B 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-V2.5 was released on 2024-05-08, while Qwen3 VL 32B Instruct was released on 2025-09-22.
Qwen3 VL 32B Instruct is 17 months newer than DeepSeek-V2.5.
May 8, 2024
2.0 years ago
Sep 22, 2025
7 months ago
1.4yr 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
Qwen3 VL 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V2.5 vs Qwen3 VL 32B Instruct.