Model Comparison

DeepSeek VL2 Small vs MiniMax M1 40K

Comparing DeepSeek VL2 Small and MiniMax M1 40K across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Small and MiniMax M1 40K don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Small
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
MiniMax
MiniMax M1 40K
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

440.0B diff

MiniMax M1 40K has 440.0B more parameters than DeepSeek VL2 Small, making it 2750.0% larger.

DeepSeek
DeepSeek VL2 Small
16.0Bparameters
MiniMax
MiniMax M1 40K
456.0Bparameters
16.0B
DeepSeek VL2 Small
456.0B
MiniMax M1 40K

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Small supports multimodal inputs, whereas MiniMax M1 40K does not.

DeepSeek VL2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2 Small

Text
Images
Audio
Video

MiniMax M1 40K

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small is licensed under deepseek, while MiniMax M1 40K uses MIT.

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

DeepSeek VL2 Small

deepseek

Open weights

MiniMax M1 40K

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Small was released on 2024-12-13, while MiniMax M1 40K was released on 2025-06-16.

MiniMax M1 40K is 6 months newer than DeepSeek VL2 Small.

DeepSeek VL2 Small

Dec 13, 2024

1.3 years ago

MiniMax M1 40K

Jun 16, 2025

10 months ago

6mo 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

DeepSeek
Supports multimodal inputs
MiniMax

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Small
MiniMax
MiniMax M1 40K

FAQ

Common questions about DeepSeek VL2 Small vs MiniMax M1 40K

DeepSeek VL2 Small (DeepSeek) and MiniMax M1 40K (MiniMax) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. 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%.
Key differences include multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Small is developed by DeepSeek and MiniMax M1 40K is developed by MiniMax.