Model Comparison
Ministral 3 (8B Base 2512) vs Qwen3-Coder
Comparing Ministral 3 (8B Base 2512) and Qwen3-Coder across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Ministral 3 (8B Base 2512) and Qwen3-Coder 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
Qwen3-Coder has 472.0B more parameters than Ministral 3 (8B Base 2512), making it 5900.0% larger.
Context Window
Maximum input and output token capacity
Only Qwen3-Coder specifies input context (256,000 tokens). Only Qwen3-Coder specifies output context (256,000 tokens).
Input Capabilities
Supported data types and modalities
Ministral 3 (8B Base 2512) supports multimodal inputs, whereas Qwen3-Coder does not.
Ministral 3 (8B Base 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ministral 3 (8B Base 2512)
Qwen3-Coder
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 (8B Base 2512) was released on 2025-12-04, while Qwen3-Coder was released on 2025-01-01.
Ministral 3 (8B Base 2512) is 11 months newer than Qwen3-Coder.
Dec 4, 2025
4 months ago
11mo newerJan 1, 2025
1.3 years 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 (8B Base 2512)
View detailsMistral AI
Qwen3-Coder
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Ministral 3 (8B Base 2512) vs Qwen3-Coder