DeepSeek-V3.2 (Non-thinking) vs Mistral Large 3 (675B Instruct 2512 Eagle) Comparison
Comparing DeepSeek-V3.2 (Non-thinking) and Mistral Large 3 (675B Instruct 2512 Eagle) across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2 (Non-thinking) and Mistral Large 3 (675B Instruct 2512 Eagle) 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-V3.2 (Non-thinking) has 10.0B more parameters than Mistral Large 3 (675B Instruct 2512 Eagle), making it 1.5% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V3.2 (Non-thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Non-thinking) specifies output context (8,192 tokens).
Input Capabilities
Supported data types and modalities
Mistral Large 3 (675B Instruct 2512 Eagle) supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) does not.
Mistral Large 3 (675B Instruct 2512 Eagle) can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2 (Non-thinking)
Mistral Large 3 (675B Instruct 2512 Eagle)
License
Usage and distribution terms
DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while Mistral Large 3 (675B Instruct 2512 Eagle) uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while Mistral Large 3 (675B Instruct 2512 Eagle) was released on 2025-12-04.
Mistral Large 3 (675B Instruct 2512 Eagle) is 0 month newer than DeepSeek-V3.2 (Non-thinking).
Dec 1, 2025
3 months ago
Dec 4, 2025
3 months ago
3d 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
Detailed Comparison
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