What are the hardware requirements for DoublePotato Mistral Nemo 13B?

DoublePotato Mistral Nemo 13B requires approximately 26.8 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DoublePotato Mistral Nemo 13B and how large is it?

DoublePotato Mistral Nemo 13B is developed by nbeerbower, a model with 12b 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 DoublePotato Mistral Nemo 13B?

DoublePotato Mistral Nemo 13B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DoublePotato Mistral Nemo 13B by nbeerbower — VRAM 26.8GB, 1000K context

Name: DoublePotato Mistral Nemo 13B
Author: nbeerbower

DoublePotato Mistral Nemo 13B is an open-source language model by nbeerbower. Features: 12b LLM, VRAM: 26.8GB, Context: 1000K, Merged, LLM Explorer Score: 0.24.

Merged Model Base model:finetune:nbeerbower... Base model:nbeerbower/mistral-... Conversational Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nbeerbower/DoublePotato-Mistral-Nemo-13B

DoublePotato Mistral Nemo 13B Parameters and Internals

LLM Name	DoublePotato Mistral Nemo 13B
Repository 🤗	https://huggingface.co/nbeerbower/DoublePotato-Mistral-Nemo-13B
Base Model(s)	Mistral Nemo Kartoffel 12B nbeerbower/mistral-nemo-kartoffel-12B
Merged Model	Yes
Model Size	12b
Required VRAM	26.8 GB
Updated	2026-08-03
Maintainer	nbeerbower
Model Type	mistral
Model Files	4.9 GB: 1-of-6 4.9 GB: 2-of-6 5.0 GB: 3-of-6 4.9 GB: 4-of-6 4.9 GB: 5-of-6 2.2 GB: 6-of-6
Model Architecture	MistralForCausalLM
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.48.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the DoublePotato Mistral Nemo 13B 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

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Note: green Score (e.g. "73.2") means that the model is better than nbeerbower/DoublePotato-Mistral-Nemo-13B.