MiniMax M1 40K vs Qwen3.5-4B Comparison

Comparing MiniMax M1 40K and Qwen3.5-4B across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

MiniMax M1 40K outperforms in 2 benchmarks (LongBench v2, MMLU-Pro), while Qwen3.5-4B is better at 2 benchmarks (GPQA, Multi-Challenge).

Both models are evenly matched across the benchmarks.

Tue Mar 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Mar 17 2026 • llm-stats.com
MiniMax
MiniMax M1 40K
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3.5-4B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

452.0B diff

MiniMax M1 40K has 452.0B more parameters than Qwen3.5-4B, making it 11300.0% larger.

MiniMax
MiniMax M1 40K
456.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.5-4B
4.0Bparameters
456.0B
MiniMax M1 40K
4.0B
Qwen3.5-4B

Input Capabilities

Supported data types and modalities

Qwen3.5-4B supports multimodal inputs, whereas MiniMax M1 40K does not.

Qwen3.5-4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

MiniMax M1 40K

Text
Images
Audio
Video

Qwen3.5-4B

Text
Images
Audio
Video

License

Usage and distribution terms

MiniMax M1 40K is licensed under MIT, while Qwen3.5-4B uses Apache 2.0.

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

MiniMax M1 40K

MIT

Open weights

Qwen3.5-4B

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiniMax M1 40K was released on 2025-06-16, while Qwen3.5-4B was released on 2026-03-02.

Qwen3.5-4B is 9 months newer than MiniMax M1 40K.

MiniMax M1 40K

Jun 16, 2025

9 months ago

Qwen3.5-4B

Mar 2, 2026

2 weeks ago

8mo newer

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

Outputs Comparison

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Key Takeaways

Higher LongBench v2 score (61.0% vs 50.0%)
Higher MMLU-Pro score (80.6% vs 79.1%)
Alibaba Cloud / Qwen Team

Qwen3.5-4B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Higher GPQA score (76.2% vs 69.2%)
Higher Multi-Challenge score (49.0% vs 44.7%)

Detailed Comparison

AI Model Comparison Table
Feature
MiniMax
MiniMax M1 40K
Alibaba Cloud / Qwen Team
Qwen3.5-4B