Model Comparison

MiniMax M2 vs Qwen3 32B

MiniMax M2 significantly outperforms across most benchmarks. Qwen3 32B is 3.5x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

MiniMax M2 outperforms in 2 benchmarks (AIME 2025, LiveCodeBench), while Qwen3 32B is better at 0 benchmarks.

MiniMax M2 significantly outperforms across most benchmarks.

Sat Apr 11 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 32B costs less

For input processing, MiniMax M2 ($0.30/1M tokens) is 3.0x more expensive than Qwen3 32B ($0.10/1M tokens).

For output processing, MiniMax M2 ($1.20/1M tokens) is 4.0x more expensive than Qwen3 32B ($0.30/1M tokens).

In conclusion, MiniMax M2 is more expensive than Qwen3 32B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Apr 11 2026 • llm-stats.com
MiniMax
MiniMax M2
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Alibaba Cloud / Qwen Team
Qwen3 32B
Input tokens$0.10
Output tokens$0.30
Best providerDeepinfra
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Model Size

Parameter count comparison

197.2B diff

MiniMax M2 has 197.2B more parameters than Qwen3 32B, making it 601.2% larger.

MiniMax
MiniMax M2
230.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 32B
32.8Bparameters
230.0B
MiniMax M2
32.8B
Qwen3 32B

Context Window

Maximum input and output token capacity

MiniMax M2 accepts 1,000,000 input tokens compared to Qwen3 32B's 128,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Qwen3 32B is limited to 128,000 tokens.

MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 32B
Input128,000 tokens
Output128,000 tokens
Sat Apr 11 2026 • llm-stats.com

License

Usage and distribution terms

MiniMax M2 is licensed under MIT, while Qwen3 32B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

MiniMax M2

MIT

Open weights

Qwen3 32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiniMax M2 was released on 2025-10-27, while Qwen3 32B was released on 2025-04-29.

MiniMax M2 is 6 months newer than Qwen3 32B.

MiniMax M2

Oct 27, 2025

5 months ago

6mo newer
Qwen3 32B

Apr 29, 2025

11 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

MiniMax M2 is available from MiniMax, Novita. Qwen3 32B is available from DeepInfra, Novita, Sambanova.

MiniMax M2

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen3 32B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.44/1M
sambanova logo
Sambanova
Input Price:Input: $0.40/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Larger context window (1,000,000 tokens)
Higher AIME 2025 score (78.0% vs 72.9%)
Higher LiveCodeBench score (83.0% vs 65.7%)
Alibaba Cloud / Qwen Team

Qwen3 32B

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
MiniMax
MiniMax M2
Alibaba Cloud / Qwen Team
Qwen3 32B

FAQ

Common questions about MiniMax M2 vs Qwen3 32B

MiniMax M2 significantly outperforms across most benchmarks. MiniMax M2 is made by MiniMax and Qwen3 32B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%. Qwen3 32B scores Arena Hard: 93.8%, AIME 2024: 81.4%, LiveBench: 74.9%, MultiLF: 73.0%, AIME 2025: 72.9%.
Qwen3 32B is 3.0x cheaper for input tokens. MiniMax M2 costs $0.30/M input and $1.20/M output via minimax. Qwen3 32B costs $0.10/M input and $0.30/M output via deepinfra.
MiniMax M2 supports 1.0M tokens and Qwen3 32B supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (1.0M vs 128K), input pricing ($0.30 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
MiniMax M2 is developed by MiniMax and Qwen3 32B is developed by Alibaba Cloud / Qwen Team.