Model Comparison
DeepSeek-R1-0528 vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?
DeepSeek-R1-0528 has a slight edge in benchmark performance. DeepSeek-R1-0528 is 1.3x cheaper per token.
Verdict: DeepSeek-R1-0528 vs Qwen3 VL 235B A22B Thinking — which is better?
DeepSeek-R1-0528 (by DeepSeek) and Qwen3 VL 235B A22B 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 3 benchmarks (Humanity's Last Exam, MMLU-Pro, SimpleQA), while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (AIME 2025, MMLU-Redux). DeepSeek-R1-0528 has a slight edge in benchmark performance.
On price, DeepSeek-R1-0528 is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1-0528 if…
- you want the strongest raw capability — it leads on 3 of 5 shared benchmarks
- cost matters — it's about 1.3x cheaper per token
Choose Qwen3 VL 235B A22B Thinking if…
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1-0528 outperforms in 3 benchmarks (Humanity's Last Exam, MMLU-Pro, SimpleQA), while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (AIME 2025, MMLU-Redux).
DeepSeek-R1-0528 has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 1.1x more expensive than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.6x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than DeepSeek-R1-0528.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 435.0B more parameters than Qwen3 VL 235B A22B Thinking, making it 184.3% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to DeepSeek-R1-0528's 131,072 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while DeepSeek-R1-0528 is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Qwen3 VL 235B A22B 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 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 4 months newer than DeepSeek-R1-0528.
May 28, 2025
1.2 years ago
Sep 22, 2025
10 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.
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
DeepSeek-R1-0528
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Key Takeaways
DeepSeek-R1-0528
View detailsDeepSeek
Qwen3 VL 235B A22B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-R1-0528 vs Qwen3 VL 235B A22B Thinking.