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Mistral-Small-3.2-24B-Instruct-hfGghfez
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24B Params FP8 Open Weights Inference Available

Mistral-Small-3.2-24B-Instruct-hf is a 24 billion parameter instruction-tuned causal language model developed by Mistral AI, converted to the Hugging Face format. This model is designed for general instruction following tasks, leveraging its substantial parameter count for robust language understanding and generation. It is specifically noted as not being multimodal, focusing solely on text-based interactions.

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Parameters:24BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:June 2025
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gghfez/Mistral-Small-3.2-24B-Instruct-hf
Popular Sampler Settings

Most commonly used values from Featherless users

temperature

This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.

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top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

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top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

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frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

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presence_penalty

This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.

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repetition_penalty

This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.

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min_p

This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.

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