Model Comparison
DeepSeek-R1 vs Qwen3 235B A22BWhich is better in 2026?
Comparing DeepSeek-R1 and Qwen3 235B A22B across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-R1 vs Qwen3 235B A22B — which is better?
DeepSeek-R1 (by DeepSeek) and Qwen3 235B A22B (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.
On price, Qwen3 235B A22B is roughly 9.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1 if…
- you process long inputs — it offers a 131,072 token context window
Choose Qwen3 235B A22B if…
- cost matters — it's about 9.6x cheaper per token
- you want the most recent training data — it shipped Apr 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Qwen3 235B A22Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 21.9x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than Qwen3 235B A22B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 436.0B more parameters than Qwen3 235B A22B, making it 185.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1 accepts 131,072 input tokens compared to Qwen3 235B A22B's 128,000 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while Qwen3 235B A22B is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Qwen3 235B A22B 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 was released on 2025-01-20, while Qwen3 235B A22B was released on 2025-04-29.
Qwen3 235B A22B is 3 months newer than DeepSeek-R1.
Jan 20, 2025
1.4 years ago
Apr 29, 2025
1.1 years 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 is available from DeepSeek, DeepInfra, Together, Fireworks. Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together.
DeepSeek-R1
Qwen3 235B A22B
Outputs Comparison
Key Takeaways
DeepSeek-R1
View detailsDeepSeek
Qwen3 235B A22B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1 vs Qwen3 235B A22B.