DeepSeek VL2 vs MiniStral 3 (14B Instruct 2512) Comparison
Comparing DeepSeek VL2 and MiniStral 3 (14B Instruct 2512) across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek VL2 and MiniStral 3 (14B 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.
Model Size
Parameter count comparison
DeepSeek VL2 has 13.0B more parameters than MiniStral 3 (14B Instruct 2512), making it 92.9% larger.
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).
Input Capabilities
Supported data types and modalities
Both DeepSeek VL2 and MiniStral 3 (14B Instruct 2512) support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek VL2
MiniStral 3 (14B Instruct 2512)
License
Usage and distribution terms
DeepSeek VL2 is licensed under deepseek, while MiniStral 3 (14B Instruct 2512) uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek VL2 was released on 2024-12-13, while MiniStral 3 (14B Instruct 2512) was released on 2025-12-04.
MiniStral 3 (14B Instruct 2512) is 12 months newer than DeepSeek VL2.
Dec 13, 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 VL2
View detailsDeepSeek
Detailed Comparison
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