What are the hardware requirements for Shisa V2 Mistral Nemo 12B Abliterated?

Shisa V2 Mistral Nemo 12B Abliterated requires approximately 24.5 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 Shisa V2 Mistral Nemo 12B Abliterated and how large is it?

Shisa V2 Mistral Nemo 12B Abliterated is developed by yamatazen, 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 Shisa V2 Mistral Nemo 12B Abliterated?

Shisa V2 Mistral Nemo 12B Abliterated is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Shisa V2 Mistral Nemo 12B Abliterated by yamatazen — VRAM 24.5GB, 128K context

Name: Shisa V2 Mistral Nemo 12B Abliterated
Author: yamatazen

Shisa V2 Mistral Nemo 12B Abliterated is an open-source language model by yamatazen. Features: 12b LLM, VRAM: 24.5GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.18.

Merged Model Arxiv:2306.01708 Abliterated Base model:natong19/mistral-ne... Base model:shisa-ai/shisa-v2-m... Conversational En Endpoints compatible Instruct Ja Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated

Shisa V2 Mistral Nemo 12B Abliterated Parameters and Internals

LLM Name	Shisa V2 Mistral Nemo 12B Abliterated
Repository 🤗	https://huggingface.co/yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated
Base Model(s)	Shisa V2 Mistral Nemo 12B ...Nemo Instruct 2407 Abliterated shisa-ai/shisa-v2-mistral-nemo-12b natong19/Mistral-Nemo-Instruct-2407-abliterated
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2026-08-05
Maintainer	yamatazen
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Supported Languages	en ja
Model Architecture	MistralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.51.1
Tokenizer Class	PreTrainedTokenizer
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Shisa V2 Mistral Nemo 12B Abliterated capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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 Shisa V2 Mistral Nemo 12B Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
...r Nemo 12B Instruct R 21 09 24	1000K / 24.5 GB	396277	141
Qliphoth 12B V1.1	1000K / 24.5 GB	22	3
Qliphoth 12B V1	1000K / 24.5 GB	26	2
SauerkrautLM Nemo 12B Instruct	1000K / 24.5 GB	1473	22
Magnum V4 12B	1000K / 24.5 GB	1116	54
MN Slush	1000K / 24.5 GB	181	32
ChatWaifu V1.4	1000K / 24.5 GB	335	20
ChatWaifu 12B V2.0	1000K / 24.5 GB	175	22
Mistral Nemo Bophades 12B	1000K / 24.5 GB	18	9
Impish Nemo 12B	1000K / 24.5 GB	355	84

Note: green Score (e.g. "73.2") means that the model is better than yamatazen/Shisa-v2-Mistral-Nemo-12B-Abliterated.