Mistral-Small-24B-Instruct-2501 is an instruction-tuned language model hosted on Hugging Face. It follows the MistralForCausalLM architecture with a mistral model type and includes a tokenizer featuring a beginning-of-sequence token and a chat template. The system prompt embedded in the template identifies it as Mistral Small 3, a large language model created by Mistral AI, a French startup headquartered in Paris. Its knowledge cutoff is stated as October 2023 and it instructs the model to admit when information is unavailable rather than fabricate details.
The model supplies a default system message that directs it to seek clarification on ambiguous or context-lacking queries instead of guessing. A vLLM tag appears among its repository metadata, indicating compatibility with that inference optimization library. The repository itself is maintained under the mistralai organization on Hugging Face, where the model card and configuration files are publicly accessible.
It belongs to the class of foundation models made available for download and local or hosted execution. Developers can obtain the weights directly from the platform to integrate into applications that require text generation or conversational responses following the provided chat template.
In the Text generation space, Mistral Small 24B Instruct 2501 takes a focused approach. It focuses on accessing a capable, open-weight instruction-tuned language model for complex reasoning and generation tasks. Mistral Small 24B Instruct 2501 is an open-source project aimed at developers. Mistral Small 24B Instruct 2501 is open source under the Apache-2.0 license. Mistral Small 24B Instruct 2501 is available on the web, the command line, and API.
Mistral AI builds and maintains Mistral Small 24B Instruct 2501, and it first shipped in 2024. Development happens publicly on GitHub with 922 stars and 32 commits in the last 90 days. PulseGate's similarity index places it among 6 comparable projects. Key capabilities include instruction following, large context window, and text generation.
Summary written by a language model from the project’s public pages.
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