Model Comparison
DeepSeek R1 Distill Qwen 32B vs Qwen3 VL 32B ThinkingWhich is better in 2026?
Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Verdict: DeepSeek R1 Distill Qwen 32B vs Qwen3 VL 32B Thinking — which is better?
DeepSeek R1 Distill Qwen 32B (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 Distill Qwen 32B outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 1 benchmark (GPQA). Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Choose DeepSeek R1 Distill Qwen 32B if…
- you want predictable pricing at $0.12/M input and $0.18/M output
Choose Qwen3 VL 32B Thinking if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 32B outperforms in 0 benchmarks, while Qwen3 VL 32B Thinking is better at 1 benchmark (GPQA).
Qwen3 VL 32B Thinking significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Qwen3 VL 32B Thinking has 0.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 0.6% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek R1 Distill Qwen 32B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Qwen 32B specifies output context (128,000 tokens).
Input Capabilities
Supported data types and modalities
Qwen3 VL 32B Thinking supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B 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 Distill Qwen 32B
Qwen3 VL 32B Thinking
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 32B 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 Distill Qwen 32B was released on 2025-01-20, while Qwen3 VL 32B Thinking was released on 2025-09-22.
Qwen3 VL 32B Thinking is 8 months newer than DeepSeek R1 Distill Qwen 32B.
Jan 20, 2025
1.5 years ago
Sep 22, 2025
10 months ago
8mo 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
Qwen3 VL 32B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs Qwen3 VL 32B Thinking.