DeepSeek-V3.2 (Non-thinking) vs Mistral Small 3.1 24B Base Comparison
Comparing DeepSeek-V3.2 (Non-thinking) and Mistral Small 3.1 24B Base across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2 (Non-thinking) and Mistral Small 3.1 24B Base 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
For input processing, DeepSeek-V3.2 (Non-thinking) ($0.28/1M tokens) is 2.8x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 1.4x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, DeepSeek-V3.2 (Non-thinking) is more expensive than Mistral Small 3.1 24B Base.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.2 (Non-thinking) has 661.0B more parameters than Mistral Small 3.1 24B Base, making it 2754.2% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3.2 (Non-thinking) accepts 131,072 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. Mistral Small 3.1 24B Base can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Mistral Small 3.1 24B Base supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) does not.
Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2 (Non-thinking)
Mistral Small 3.1 24B Base
License
Usage and distribution terms
DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while Mistral Small 3.1 24B Base 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 Small 3.1 24B Base was released on 2025-03-17.
DeepSeek-V3.2 (Non-thinking) is 9 months newer than Mistral Small 3.1 24B Base.
Dec 1, 2025
3 months ago
8mo newerMar 17, 2025
12 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3.2 (Non-thinking) is available from DeepSeek. Mistral Small 3.1 24B Base is available from Mistral AI. The availability of providers can affect quality of the model and reliability.
DeepSeek-V3.2 (Non-thinking)
Mistral Small 3.1 24B Base
Outputs Comparison
Key Takeaways
Mistral Small 3.1 24B Base
View detailsMistral AI
Detailed Comparison
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