DeepSeek-V3 vs Ministral 3 (3B Base 2512) Comparison
Comparing DeepSeek-V3 and Ministral 3 (3B Base 2512) across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3 outperforms in 2 benchmarks (MMLU, MMLU-Redux), while Ministral 3 (3B Base 2512) is better at 0 benchmarks.
DeepSeek-V3 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
DeepSeek-V3 has 668.0B more parameters than Ministral 3 (3B Base 2512), making it 22266.7% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Ministral 3 (3B Base 2512) supports multimodal inputs, whereas DeepSeek-V3 does not.
Ministral 3 (3B Base 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3
Ministral 3 (3B Base 2512)
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Ministral 3 (3B Base 2512) uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Ministral 3 (3B Base 2512) was released on 2025-12-04.
Ministral 3 (3B Base 2512) is 11 months newer than DeepSeek-V3.
Dec 25, 2024
1.2 years ago
Dec 4, 2025
3 months ago
11mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek-V3
View detailsDeepSeek
Ministral 3 (3B Base 2512)
View detailsMistral AI
Detailed Comparison
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