DeepSeek-R1 vs Mistral Small 3.1 24B Instruct Comparison
Comparing DeepSeek-R1 and Mistral Small 3.1 24B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1 and Mistral Small 3.1 24B Instruct 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-R1 has 647.0B more parameters than Mistral Small 3.1 24B Instruct, making it 2695.8% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1 specifies input context (131,072 tokens). Only DeepSeek-R1 specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Mistral Small 3.1 24B Instruct supports multimodal inputs, whereas DeepSeek-R1 does not.
Mistral Small 3.1 24B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
Mistral Small 3.1 24B Instruct
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while Mistral Small 3.1 24B Instruct 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-R1 was released on 2025-01-20, while Mistral Small 3.1 24B Instruct was released on 2025-03-17.
Mistral Small 3.1 24B Instruct is 2 months newer than DeepSeek-R1.
Jan 20, 2025
1.2 years ago
Mar 17, 2025
1.0 years ago
1mo 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-R1
View detailsDeepSeek
Detailed Comparison
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