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Devstral-Small-2505Unsloth
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24B Params FP8 Open Weights Inference Available

Devstral-Small-2505 is a 24 billion parameter agentic LLM developed by Mistral AI and All Hands AI, fine-tuned from Mistral-Small-3.1. It is specifically designed for software engineering tasks, excelling at using tools to explore codebases and edit multiple files. The model achieves a 46.8% score on SWE-Bench Verified, positioning it as a leading open-source model for code generation and agentic capabilities, with a 128k token context window.

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Parameters:24BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:May 2025
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unsloth/Devstral-Small-2505
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.

top_p

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

top_k

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

frequency_penalty

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

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.

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.

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.