Model Comparison

MiniMax M1 40K vs Qwen3 VL 4B ThinkingWhich is better in 2026?

MiniMax M1 40K significantly outperforms across most benchmarks.

Verdict: MiniMax M1 40K vs Qwen3 VL 4B Thinking — which is better?

MiniMax M1 40K (by MiniMax) and Qwen3 VL 4B 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 M1 40K outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 4B Thinking is better at 0 benchmarks. MiniMax M1 40K significantly outperforms across most benchmarks.

Choose MiniMax M1 40K if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks

Choose Qwen3 VL 4B Thinking if…

  • you want the most recent training data — it shipped Sep 2025

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

MiniMax M1 40K outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 4B Thinking is better at 0 benchmarks.

MiniMax M1 40K significantly outperforms across most benchmarks.

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

452.0B diff

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

MiniMax
MiniMax M1 40K
456.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
456.0B
MiniMax M1 40K
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

MiniMax
MiniMax M1 40K
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas MiniMax M1 40K does not.

Qwen3 VL 4B Thinking 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 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

MiniMax M1 40K is licensed under MIT, while Qwen3 VL 4B Thinking 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 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiniMax M1 40K was released on 2025-06-16, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 3 months newer than MiniMax M1 40K.

MiniMax M1 40K

Jun 16, 2025

1.0 years ago

Qwen3 VL 4B Thinking

Sep 22, 2025

9 months ago

3mo 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

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Higher AIME 2025 score (74.6% vs 74.5%)
Higher GPQA score (69.2% vs 64.1%)
Higher MMLU-Pro score (80.6% vs 73.6%)
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
MiniMax
MiniMax M1 40K
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about MiniMax M1 40K vs Qwen3 VL 4B Thinking.

Which is better, MiniMax M1 40K or Qwen3 VL 4B Thinking?

MiniMax M1 40K significantly outperforms across most benchmarks. MiniMax M1 40K is made by MiniMax and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does MiniMax M1 40K compare to Qwen3 VL 4B Thinking in benchmarks?

MiniMax M1 40K scores MATH-500: 96.0%, AIME 2024: 83.3%, MMLU-Pro: 80.6%, ZebraLogic: 80.1%, OpenAI-MRCR: 2 needle 128k: 76.1%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for MiniMax M1 40K and Qwen3 VL 4B Thinking?

MiniMax M1 40K supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between MiniMax M1 40K and Qwen3 VL 4B Thinking?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes MiniMax M1 40K and Qwen3 VL 4B Thinking?

MiniMax M1 40K is developed by MiniMax and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.