Model Comparison
DeepSeek-V3.2-Speciale vs Qwen3 MaxWhich is better in 2026?
DeepSeek-V3.2-Speciale significantly outperforms across most benchmarks. DeepSeek-V3.2-Speciale is 5.2x cheaper per token.
Verdict: DeepSeek-V3.2-Speciale vs Qwen3 Max — which is better?
DeepSeek-V3.2-Speciale (by DeepSeek) and Qwen3 Max (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-V3.2-Speciale outperforms in 3 benchmarks (AIME 2025, SWE-Bench Verified, t2-bench), while Qwen3 Max is better at 0 benchmarks. DeepSeek-V3.2-Speciale significantly outperforms across most benchmarks.
On price, DeepSeek-V3.2-Speciale is roughly 5.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 Max also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.2-Speciale if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- cost matters — it's about 5.2x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Qwen3 Max if…
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Speciale outperforms in 3 benchmarks (AIME 2025, SWE-Bench Verified, t2-bench), while Qwen3 Max is better at 0 benchmarks.
DeepSeek-V3.2-Speciale significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 1.8x cheaper than Qwen3 Max ($0.50/1M tokens).
For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 11.9x cheaper than Qwen3 Max ($5.00/1M tokens).
In conclusion, Qwen3 Max is more expensive than DeepSeek-V3.2-Speciale.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max has 315.0B more parameters than DeepSeek-V3.2-Speciale, making it 46.0% larger.
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to DeepSeek-V3.2-Speciale's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-V3.2-Speciale is licensed under MIT, while Qwen3 Max uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2-Speciale was released on 2025-12-01, while Qwen3 Max was released on 2025-12-15.
Qwen3 Max is 0 month newer than DeepSeek-V3.2-Speciale.
Dec 1, 2025
7 months ago
Dec 15, 2025
7 months ago
2w 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-V3.2-Speciale is available from DeepSeek. Qwen3 Max is available from Novita.
DeepSeek-V3.2-Speciale
Qwen3 Max
Outputs Comparison
Key Takeaways
Qwen3 Max
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Speciale and Qwen3 Max side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V3.2-Speciale vs Qwen3 Max.