DeepSeek-V3.1 vs Qwen3-Next-80B-A3B-Instruct
DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 is 1.1x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V3.1 outperforms in 4 benchmarks (Aider-Polyglot, GPQA, MMLU-Pro, MMLU-Redux), while Qwen3-Next-80B-A3B-Instruct is better at 1 benchmark (AIME 2025). DeepSeek-V3.1 significantly outperforms across most benchmarks.
On price, DeepSeek-V3.1 is roughly 1.1x 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.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V3.1
- you want the strongest raw capability — it leads on 4 of 5 shared benchmarks
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 163,840 token context window
Choose Qwen3-Next-80B-A3B-Instruct
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.1 outperforms in 4 benchmarks (Aider-Polyglot, GPQA, MMLU-Pro, MMLU-Redux), while Qwen3-Next-80B-A3B-Instruct is better at 1 benchmark (AIME 2025).
DeepSeek-V3.1 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 1.8x more expensive than Qwen3-Next-80B-A3B-Instruct ($0.15/1M tokens).
For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 1.5x cheaper than Qwen3-Next-80B-A3B-Instruct ($1.50/1M tokens).
In conclusion, Qwen3-Next-80B-A3B-Instruct is more expensive than DeepSeek-V3.1.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.1 has 591.0B more parameters than Qwen3-Next-80B-A3B-Instruct, making it 738.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3.1 accepts 163,840 input tokens compared to Qwen3-Next-80B-A3B-Instruct's 65,536 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Qwen3-Next-80B-A3B-Instruct is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V3.1 is licensed under MIT, while Qwen3-Next-80B-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-V3.1 was released on 2025-01-10, while Qwen3-Next-80B-A3B-Instruct was released on 2025-09-10.
Qwen3-Next-80B-A3B-Instruct is 8 months newer than DeepSeek-V3.1.
Jan 10, 2025
1.6 years ago
Sep 10, 2025
11 months ago
8mo 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-Next-80B-A3B-Instruct is available from Novita.
DeepSeek-V3.1
Qwen3-Next-80B-A3B-Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.1 and Qwen3-Next-80B-A3B-Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.1 vs Qwen3-Next-80B-A3B-Instruct.