Model Comparison
DeepSeek-R1-0528 vs Qwen3 VL 30B A3B InstructWhich is better in 2026?
DeepSeek-R1-0528 significantly outperforms across most benchmarks. Qwen3 VL 30B A3B Instruct is 2.8x cheaper per token.
Verdict: DeepSeek-R1-0528 vs Qwen3 VL 30B A3B Instruct — which is better?
DeepSeek-R1-0528 (by DeepSeek) and Qwen3 VL 30B A3B Instruct (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 30B A3B Instruct is better at 0 benchmarks. DeepSeek-R1-0528 significantly outperforms across most benchmarks.
On price, Qwen3 VL 30B A3B Instruct is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-R1-0528 if…
- you want the strongest raw capability — it leads on 5 of 5 shared benchmarks
Choose Qwen3 VL 30B A3B Instruct if…
- cost matters — it's about 2.8x cheaper per token
- 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 30B A3B Instruct is better at 0 benchmarks.
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 2.5x more expensive than Qwen3 VL 30B A3B Instruct ($0.20/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 3.1x more expensive than Qwen3 VL 30B A3B Instruct ($0.70/1M tokens).
In conclusion, DeepSeek-R1-0528 is more expensive than Qwen3 VL 30B A3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 640.0B more parameters than Qwen3 VL 30B A3B Instruct, making it 2064.5% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Instruct is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 30B A3B Instruct supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Qwen3 VL 30B A3B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Qwen3 VL 30B A3B Instruct
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Qwen3 VL 30B A3B Instruct 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 30B A3B Instruct was released on 2025-09-22.
Qwen3 VL 30B A3B Instruct 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.
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Qwen3 VL 30B A3B Instruct is available from Novita, DeepInfra.
DeepSeek-R1-0528
Qwen3 VL 30B A3B Instruct
Outputs Comparison
Key Takeaways
DeepSeek-R1-0528
View detailsDeepSeek
Qwen3 VL 30B A3B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1-0528 vs Qwen3 VL 30B A3B Instruct.