Model Comparison
MiniMax M1 80K vs Qwen3 235B A22BWhich is better in 2026?
MiniMax M1 80K has a slight edge in benchmark performance. Qwen3 235B A22B is 9.6x cheaper per token.
Verdict: MiniMax M1 80K vs Qwen3 235B A22B — which is better?
MiniMax M1 80K (by MiniMax) and Qwen3 235B A22B (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 M1 80K outperforms in 3 benchmarks (AIME 2024, GPQA, MMLU-Pro), while Qwen3 235B A22B is better at 2 benchmarks (AIME 2025, LiveCodeBench). MiniMax M1 80K has a slight edge in benchmark performance.
On price, Qwen3 235B A22B is roughly 9.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M1 80K also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M1 80K if…
- you want the strongest raw capability — it leads on 3 of 5 shared benchmarks
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Jun 2025
Choose Qwen3 235B A22B if…
- cost matters — it's about 9.6x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M1 80K outperforms in 3 benchmarks (AIME 2024, GPQA, MMLU-Pro), while Qwen3 235B A22B is better at 2 benchmarks (AIME 2025, LiveCodeBench).
MiniMax M1 80K has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M1 80K ($0.55/1M tokens) is 5.5x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
For output processing, MiniMax M1 80K ($2.20/1M tokens) is 22.0x more expensive than Qwen3 235B A22B ($0.10/1M tokens).
In conclusion, MiniMax M1 80K is more expensive than Qwen3 235B A22B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M1 80K has 221.0B more parameters than Qwen3 235B A22B, making it 94.0% larger.
Context Window
Maximum input and output token capacity
MiniMax M1 80K accepts 1,000,000 input tokens compared to Qwen3 235B A22B's 128,000 tokens. Qwen3 235B A22B can generate longer responses up to 128,000 tokens, while MiniMax M1 80K is limited to 40,000 tokens.
License
Usage and distribution terms
MiniMax M1 80K is licensed under MIT, while Qwen3 235B A22B 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 M1 80K was released on 2025-06-16, while Qwen3 235B A22B was released on 2025-04-29.
MiniMax M1 80K is 2 months newer than Qwen3 235B A22B.
Jun 16, 2025
1.1 years ago
1mo newerApr 29, 2025
1.2 years 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 M1 80K is available from Novita. Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together.
MiniMax M1 80K
Qwen3 235B A22B
Outputs Comparison
Key Takeaways
MiniMax M1 80K
View detailsMiniMax
Qwen3 235B A22B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M1 80K and Qwen3 235B A22B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiniMax M1 80K vs Qwen3 235B A22B.