Model Comparison
DeepSeek-V3.1 vs Qwen3 30B A3BWhich is better in 2026?
Qwen3 30B A3B shows notably better performance in the majority of benchmarks. Qwen3 30B A3B is 3.0x cheaper per token.
Verdict: DeepSeek-V3.1 vs Qwen3 30B A3B — which is better?
DeepSeek-V3.1 (by DeepSeek) and Qwen3 30B A3B (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-V3.1 outperforms in 1 benchmarks (GPQA), while Qwen3 30B A3B is better at 3 benchmarks (AIME 2024, AIME 2025, LiveCodeBench). Qwen3 30B A3B shows notably better performance in the majority of benchmarks.
On price, Qwen3 30B A3B is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.1 also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.1 if…
- you process long inputs — it offers a 163,840 token context window
Choose Qwen3 30B A3B if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- cost matters — it's about 3.0x cheaper per token
- you want the most recent training data — it shipped Apr 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.1 outperforms in 1 benchmarks (GPQA), while Qwen3 30B A3B is better at 3 benchmarks (AIME 2024, AIME 2025, LiveCodeBench).
Qwen3 30B A3B shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 2.7x more expensive than Qwen3 30B A3B ($0.10/1M tokens).
For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 3.3x more expensive than Qwen3 30B A3B ($0.30/1M tokens).
In conclusion, DeepSeek-V3.1 is more expensive than Qwen3 30B A3B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.1 has 640.5B more parameters than Qwen3 30B A3B, making it 2100.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3.1 accepts 163,840 input tokens compared to Qwen3 30B A3B's 128,000 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Qwen3 30B A3B is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-V3.1 is licensed under MIT, while Qwen3 30B A3B 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-V3.1 was released on 2025-01-10, while Qwen3 30B A3B was released on 2025-04-29.
Qwen3 30B A3B is 4 months newer than DeepSeek-V3.1.
Jan 10, 2025
1.5 years ago
Apr 29, 2025
1.2 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-V3.1 is available from DeepInfra, Novita. Qwen3 30B A3B is available from DeepInfra, Novita, Fireworks.
DeepSeek-V3.1
Qwen3 30B A3B
Outputs Comparison
Key Takeaways
DeepSeek-V3.1
View detailsDeepSeek
Qwen3 30B A3B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3.1 and Qwen3 30B A3B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3.1 vs Qwen3 30B A3B.