Mistral Small3.2 24B Instruct - Model Details

Mistral Small3.2 24B Instruct is a large language model developed by Mistral Ai, a company specializing in advanced AI research. With 24b parameters, it is designed for enhanced obedience to instructions and improved task execution. The model's licence details are not specified, but its focus on instruction-following capabilities makes it suitable for a wide range of applications requiring precise and reliable performance.

Description of Mistral Small3.2 24B Instruct

Mistral-Small-3.2-24B-Instruct-2506 is a minor update to its predecessor, Mistral-Small-3.1-24B-Instruct-2503, with targeted improvements in instruction following, repetition errors, and function calling. It retains similar performance in other categories compared to the previous version. The model emphasizes enhanced reliability and precision in task execution, making it suitable for applications requiring accurate and consistent responses. Its 24B parameter size supports complex interactions while maintaining efficiency.

Parameters & Context Length of Mistral Small3.2 24B Instruct

Mistral-Small-3.2-24B-Instruct-2506 is a large language model with 24b parameters, placing it in the large models category, which offers powerful capabilities for complex tasks but requires significant computational resources. Its 128k context length falls into the very long contexts range, enabling it to process and generate responses for extended texts, though this demands substantial memory and processing power. The combination of these features makes the model well-suited for tasks requiring deep understanding of lengthy inputs while balancing efficiency and performance.

• Parameter Size: 24b
• Context Length: 128k

Possible Intended Uses of Mistral Small3.2 24B Instruct

Mistral-Small-3.2-24B-Instruct-2506 is a large language model designed for tasks requiring precise instruction following and complex reasoning. Its 24b parameter size and 128k context length suggest it could support possible uses such as chat assistance, where it might help users navigate conversations with greater accuracy. Function calling could be another possible application, enabling the model to interact with external tools or systems in a dynamic way. Vision reasoning might also be a possible use case, allowing the model to analyze and interpret visual data alongside textual inputs. These possible uses would need thorough testing to ensure they align with specific requirements and constraints. The model’s design emphasizes adaptability, but its effectiveness in these areas remains to be validated through real-world experimentation.

• chat assistance
• function calling
• vision reasoning

Possible Applications of Mistral Small3.2 24B Instruct

Mistral-Small-3.2-24B-Instruct-2506 is a large language model with 24b parameters and a 128k context length, making it a possible candidate for tasks requiring nuanced instruction handling and extended text processing. Possible applications could include interactive chat assistance, where its design might support more accurate and context-aware responses. It could also serve as a possible tool for function calling, enabling seamless integration with external systems or APIs. Vision reasoning might be another possible use, allowing the model to analyze and interpret visual data alongside textual inputs. Additionally, it could be explored for possible tasks involving complex data analysis or content generation, though these possible uses would require rigorous testing to ensure alignment with specific needs. Each possible application must be thoroughly evaluated and tested before deployment to ensure reliability and suitability.

• chat assistance
• function calling
• vision reasoning
• data analysis or content generation

Quantized Versions & Hardware Requirements of Mistral Small3.2 24B Instruct

Mistral-Small-3.2-24B-Instruct-2506 requires a medium q4 version with a balance between precision and performance, which typically demands a GPU with at least 24GB VRAM (e.g., RTX 3090 Ti, A100) and system memory of at least 32GB. This setup ensures efficient execution while maintaining reasonable accuracy. Possible applications for this version would need hardware capable of handling 20GB–36GB VRAM for optimal performance. Readers should verify their graphics card specifications against these requirements to determine compatibility.

• q4, q8, q16, q32

Conclusion

Mistral-Small-3.2-24B-Instruct-2506 is a large language model with 24b parameters and a 128k context length, designed for enhanced instruction following and complex task execution. It represents a minor update with improvements in repetition errors and function calling, balancing performance and efficiency for diverse applications.

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