Model Comparison
MiniMax M2 vs Qwen3-Next-80B-A3B-ThinkingWhich is better in 2026?
Both models are evenly matched across the benchmarks. Qwen3-Next-80B-A3B-Thinking is 1.1x cheaper per token.
Verdict: MiniMax M2 vs Qwen3-Next-80B-A3B-Thinking — which is better?
MiniMax M2 (by MiniMax) 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.
MiniMax M2 outperforms in 2 benchmarks (GPQA, Tau2 Telecom), while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (AIME 2025, MMLU-Pro). Both models are evenly matched across the benchmarks.
On price, Qwen3-Next-80B-A3B-Thinking is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M2 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M2 if…
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2025
Choose Qwen3-Next-80B-A3B-Thinking if…
- cost matters — it's about 1.1x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2 outperforms in 2 benchmarks (GPQA, Tau2 Telecom), while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (AIME 2025, MMLU-Pro).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2 ($0.30/1M tokens) is 2.0x more expensive than Qwen3-Next-80B-A3B-Thinking ($0.15/1M tokens).
For output processing, MiniMax M2 ($1.20/1M tokens) is 1.3x cheaper than Qwen3-Next-80B-A3B-Thinking ($1.50/1M tokens).
In conclusion, MiniMax M2 is more expensive than Qwen3-Next-80B-A3B-Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M2 has 150.0B more parameters than Qwen3-Next-80B-A3B-Thinking, making it 187.5% larger.
Context Window
Maximum input and output token capacity
MiniMax M2 accepts 1,000,000 input tokens compared to Qwen3-Next-80B-A3B-Thinking's 65,536 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Qwen3-Next-80B-A3B-Thinking is limited to 65,536 tokens.
License
Usage and distribution terms
MiniMax M2 is licensed under MIT, 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.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiniMax M2 was released on 2025-10-27, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.
MiniMax M2 is 2 months newer than Qwen3-Next-80B-A3B-Thinking.
Oct 27, 2025
9 months ago
1mo newerSep 10, 2025
10 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M2 is available from MiniMax, Novita. Qwen3-Next-80B-A3B-Thinking is available from Novita.
MiniMax M2
Qwen3-Next-80B-A3B-Thinking
Outputs Comparison
Key Takeaways
MiniMax M2
View detailsMiniMax
Qwen3-Next-80B-A3B-Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M2 and Qwen3-Next-80B-A3B-Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiniMax M2 vs Qwen3-Next-80B-A3B-Thinking.