Model Comparison
Ministral 3 (3B Base 2512) vs Qwen3 VL 4B Instruct
Qwen3 VL 4B Instruct significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
Ministral 3 (3B Base 2512) outperforms in 0 benchmarks, while Qwen3 VL 4B Instruct is better at 2 benchmarks (MMLU, MMLU-Redux).
Qwen3 VL 4B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Qwen3 VL 4B Instruct has 1.0B more parameters than Ministral 3 (3B Base 2512), making it 33.3% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 4B Instruct specifies input context (262,144 tokens). Only Qwen3 VL 4B Instruct specifies output context (262,144 tokens).
Input Capabilities
Supported data types and modalities
Both Ministral 3 (3B Base 2512) and Qwen3 VL 4B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Ministral 3 (3B Base 2512)
Qwen3 VL 4B Instruct
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Ministral 3 (3B Base 2512) was released on 2025-12-04, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Ministral 3 (3B Base 2512) is 2 months newer than Qwen3 VL 4B Instruct.
Dec 4, 2025
5 months ago
2mo newerSep 22, 2025
8 months ago
Knowledge 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
Ministral 3 (3B Base 2512)
View detailsMistral AI
No standout differentiators in the data we have for this pair.
Qwen3 VL 4B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Ministral 3 (3B Base 2512) vs Qwen3 VL 4B Instruct.