Model Comparison
DeepSeek-V2.5 vs Qwen3-Next-80B-A3B-ThinkingWhich is better in 2026?
Comparing DeepSeek-V2.5 and Qwen3-Next-80B-A3B-Thinking across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V2.5 vs Qwen3-Next-80B-A3B-Thinking — which is better?
DeepSeek-V2.5 (by DeepSeek) and Qwen3-Next-80B-A3B-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.
On price, DeepSeek-V2.5 is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-Next-80B-A3B-Thinking also accepts a larger context window (65,536 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V2.5 if…
- cost matters — it's about 2.8x cheaper per token
Choose Qwen3-Next-80B-A3B-Thinking if…
- you process long inputs — it offers a 65,536 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 and Qwen3-Next-80B-A3B-Thinking don'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-V2.5 ($0.14/1M tokens) is 1.1x cheaper than Qwen3-Next-80B-A3B-Thinking ($0.15/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 5.4x cheaper than Qwen3-Next-80B-A3B-Thinking ($1.50/1M tokens).
In conclusion, Qwen3-Next-80B-A3B-Thinking is more expensive than DeepSeek-V2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V2.5 has 156.0B more parameters than Qwen3-Next-80B-A3B-Thinking, making it 195.0% larger.
Context Window
Maximum input and output token capacity
Qwen3-Next-80B-A3B-Thinking accepts 65,536 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Qwen3-Next-80B-A3B-Thinking can generate longer responses up to 65,536 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Qwen3-Next-80B-A3B-Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.
Qwen3-Next-80B-A3B-Thinking is 16 months newer than DeepSeek-V2.5.
May 8, 2024
2.1 years ago
Sep 10, 2025
9 months ago
1.3yr 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-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Qwen3-Next-80B-A3B-Thinking is available from Novita.
DeepSeek-V2.5
Qwen3-Next-80B-A3B-Thinking
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
Qwen3-Next-80B-A3B-Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about DeepSeek-V2.5 vs Qwen3-Next-80B-A3B-Thinking.