Model Comparison

Qwen3.5-397B-A17B vs MiniMax M2.1

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks. MiniMax M2.1 is 2.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Qwen3.5-397B-A17B outperforms in 6 benchmarks (AA-LCR, BrowseComp, GPQA, Humanity's Last Exam, IFBench, SWE-Bench Verified), while MiniMax M2.1 is better at 3 benchmarks (MMLU-Pro, SWE-bench Multilingual, Toolathlon).

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiniMax M2.1 costs less

For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 2.0x more expensive than MiniMax M2.1 ($0.30/1M tokens).

For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 3.0x more expensive than MiniMax M2.1 ($1.20/1M tokens).

In conclusion, Qwen3.5-397B-A17B is more expensive than MiniMax M2.1.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
MiniMax
MiniMax M2.1
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

167.0B diff

Qwen3.5-397B-A17B has 167.0B more parameters than MiniMax M2.1, making it 72.6% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
MiniMax
MiniMax M2.1
230.0Bparameters
397.0B
Qwen3.5-397B-A17B
230.0B
MiniMax M2.1

Context Window

Maximum input and output token capacity

MiniMax M2.1 accepts 1,000,000 input tokens compared to Qwen3.5-397B-A17B's 262,144 tokens. MiniMax M2.1 can generate longer responses up to 1,000,000 tokens, while Qwen3.5-397B-A17B is limited to 64,000 tokens.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input262,144 tokens
Output64,000 tokens
MiniMax
MiniMax M2.1
Input1,000,000 tokens
Output1,000,000 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas MiniMax M2.1 does not.

Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3.5-397B-A17B

Text
Images
Audio
Video

MiniMax M2.1

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.5-397B-A17B is licensed under Apache 2.0, while MiniMax M2.1 uses MIT.

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

Qwen3.5-397B-A17B

Apache 2.0

Open weights

MiniMax M2.1

MIT

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while MiniMax M2.1 was released on 2025-12-23.

Qwen3.5-397B-A17B is 2 months newer than MiniMax M2.1.

Qwen3.5-397B-A17B

Feb 16, 2026

1 months ago

1mo newer
MiniMax M2.1

Dec 23, 2025

3 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

Qwen3.5-397B-A17B is available from Novita. MiniMax M2.1 is available from MiniMax.

Qwen3.5-397B-A17B

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M

MiniMax M2.1

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Higher AA-LCR score (68.7% vs 62.0%)
Higher BrowseComp score (69.0% vs 62.0%)
Higher GPQA score (88.4% vs 81.0%)
Higher Humanity's Last Exam score (28.7% vs 22.0%)
Higher IFBench score (76.5% vs 70.0%)
Higher SWE-Bench Verified score (76.4% vs 67.0%)
MiniMax
Larger context window (1,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher MMLU-Pro score (88.0% vs 87.8%)
Higher SWE-bench Multilingual score (72.5% vs 69.3%)
Higher Toolathlon score (43.5% vs 38.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
MiniMax
MiniMax M2.1

FAQ

Common questions about Qwen3.5-397B-A17B vs MiniMax M2.1

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and MiniMax M2.1 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Qwen3.5-397B-A17B scores MMLU-Redux: 94.9%, HMMT 2025: 94.8%, C-Eval: 93.0%, HMMT25: 92.7%, IFEval: 92.6%. MiniMax M2.1 scores VIBE Web: 91.5%, VIBE Android: 89.7%, VIBE: 88.6%, MMLU-Pro: 88.0%, VIBE iOS: 88.0%.
MiniMax M2.1 is 2.0x cheaper for input tokens. Qwen3.5-397B-A17B costs $0.60/M input and $3.60/M output via novita. MiniMax M2.1 costs $0.30/M input and $1.20/M output via minimax.
Qwen3.5-397B-A17B supports 262K tokens and MiniMax M2.1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (262K vs 1.0M), input pricing ($0.60 vs $0.30/M), multimodal support (yes vs no), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.
Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and MiniMax M2.1 is developed by MiniMax.