Model Comparison
DeepSeek-R1-0528 vs Qwen3 VL 32B ThinkingWhich is better in 2026?
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Verdict: DeepSeek-R1-0528 vs Qwen3 VL 32B Thinking — which is better?
DeepSeek-R1-0528 (by DeepSeek) and Qwen3 VL 32B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-R1-0528 outperforms in 5 benchmarks (AIME 2025, GPQA, MMLU-Pro, MMLU-Redux, SimpleQA), while Qwen3 VL 32B Thinking is better at 0 benchmarks. DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Choose DeepSeek-R1-0528 if…
- you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
Choose Qwen3 VL 32B Thinking if…
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1-0528 outperforms in 5 benchmarks (AIME 2025, GPQA, MMLU-Pro, MMLU-Redux, SimpleQA), while Qwen3 VL 32B Thinking is better at 0 benchmarks.
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 638.0B more parameters than Qwen3 VL 32B Thinking, making it 1933.3% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1-0528 specifies input context (131,072 tokens). Only DeepSeek-R1-0528 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Qwen3 VL 32B Thinking supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Qwen3 VL 32B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Qwen3 VL 32B Thinking
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Qwen3 VL 32B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while Qwen3 VL 32B Thinking was released on 2025-09-22.
Qwen3 VL 32B Thinking is 4 months newer than DeepSeek-R1-0528.
May 28, 2025
1.0 years ago
Sep 22, 2025
8 months ago
3mo 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-R1-0528
View detailsDeepSeek
Qwen3 VL 32B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1-0528 vs Qwen3 VL 32B Thinking.