What are the hardware requirements for Mistral Small 3.1 24B RP?

Mistral Small 3.1 24B RP requires approximately 47.3 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Small 3.1 24B RP and how large is it?

Mistral Small 3.1 24B RP is developed by Aratako, a model with 24b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Mistral Small 3.1 24B RP?

Mistral Small 3.1 24B RP is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Small 3.1 24B RP by Aratako — VRAM 47.3GB, 128K context

Name: Mistral Small 3.1 24B RP
Author: Aratako

Mistral Small 3.1 24B RP is an open-source language model by Aratako. Features: 24b LLM, VRAM: 47.3GB, Context: 128K, License: mit, Instruction-Based, LLM Explorer Score: 0.18.

Base model:finetune:mistralai/... Base model:mistralai/mistral-s... Conversational Endpoints compatible Instruct Ja Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Aratako/Mistral-Small-3.1-24B-RP

Mistral Small 3.1 24B RP Parameters and Internals

LLM Name	Mistral Small 3.1 24B RP
Repository 🤗	https://huggingface.co/Aratako/Mistral-Small-3.1-24B-RP
Base Model(s)	mistralai/Mistral-Small-3.1-24B-Instruct-2503 mistralai/Mistral-Small-3.1-24B-Instruct-2503
Model Size	24b
Required VRAM	47.3 GB
Updated	2026-08-25
Maintainer	Aratako
Model Type	mistral
Instruction-Based	Yes
Model Files	4.8 GB: 1-of-10 4.8 GB: 2-of-10 4.8 GB: 3-of-10 4.9 GB: 4-of-10 4.8 GB: 5-of-10 4.8 GB: 6-of-10 4.9 GB: 7-of-10 4.8 GB: 8-of-10 4.8 GB: 9-of-10 3.9 GB: 10-of-10
Supported Languages	ja
Model Architecture	MistralForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.51.3
Tokenizer Class	LlamaTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mistral Small 3.1 24B RP capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Mistral Small 3.1 24B RP

Best Alternatives	Context / RAM	Downloads	Likes
...ral Nemo Instruct 24B Merge V1	1000K / 24.6 GB	9	0
...all 3.1 24B Instruct 2503 Text	128K / 47.3 GB	16	0
Cydonia 24B V4.3	128K / 47.3 GB	3652	138
Slimaki 24B V1.2	128K / 47.3 GB	28	6
Neural V1 24B	128K / 47.3 GB	9	3
MS3.2 PaintedFantasy V4.1 24B	128K / 47.3 GB	80	18
Cydonia 24B V4.1	128K / 47.3 GB	2162	80
Slimaki 24B V1	128K / 47.3 GB	15	10
Asmodeus 24B V1	128K / 47.3 GB	50	13
MS3.2 PaintedFantasy V3 24B	128K / 47.3 GB	28	35

Note: green Score (e.g. "73.2") means that the model is better than Aratako/Mistral-Small-3.1-24B-RP.