Model Comparison

DeepSeek VL2 vs Ministral 3 (3B Instruct 2512)

Comparing DeepSeek VL2 and Ministral 3 (3B Instruct 2512) across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Ministral 3 (3B Instruct 2512) 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
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek VL2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Ministral 3 (3B Instruct 2512)
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

24.0B diff

DeepSeek VL2 has 24.0B more parameters than Ministral 3 (3B Instruct 2512), making it 800.0% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Mistral AI
Ministral 3 (3B Instruct 2512)
3.0Bparameters
27.0B
DeepSeek VL2
3.0B
Ministral 3 (3B Instruct 2512)

Context Window

Maximum input and output token capacity

Only DeepSeek VL2 specifies input context (129,280 tokens). Only DeepSeek VL2 specifies output context (129,280 tokens).

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Mistral AI
Ministral 3 (3B Instruct 2512)
Input- tokens
Output- tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 and Ministral 3 (3B Instruct 2512) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2

Text
Images
Audio
Video

Ministral 3 (3B Instruct 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Ministral 3 (3B Instruct 2512) uses Apache 2.0.

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

DeepSeek VL2

deepseek

Open weights

Ministral 3 (3B Instruct 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Ministral 3 (3B Instruct 2512) was released on 2025-12-04.

Ministral 3 (3B Instruct 2512) is 12 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.3 years ago

Ministral 3 (3B Instruct 2512)

Dec 4, 2025

4 months ago

11mo 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
Larger context window (129,280 tokens)
Mistral AI

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Mistral AI
Ministral 3 (3B Instruct 2512)

FAQ

Common questions about DeepSeek VL2 vs Ministral 3 (3B Instruct 2512)

DeepSeek VL2 (DeepSeek) and Ministral 3 (3B Instruct 2512) (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Ministral 3 (3B Instruct 2512) scores MATH: 83.0%, Wild Bench: 56.8%, Arena Hard: 30.5%, MM-MT-Bench: 7.8%.
DeepSeek VL2 supports 129K tokens and Ministral 3 (3B Instruct 2512) supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 is developed by DeepSeek and Ministral 3 (3B Instruct 2512) is developed by Mistral AI.