What are the hardware requirements for VICIOUS MESH 12B NEMO?

VICIOUS MESH 12B NEMO 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 VICIOUS MESH 12B NEMO and how large is it?

VICIOUS MESH 12B NEMO is developed by bamec66557, 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 VICIOUS MESH 12B NEMO?

VICIOUS MESH 12B NEMO is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

VICIOUS MESH 12B NEMO by bamec66557 — VRAM 24.5GB, 128K context

Name: VICIOUS MESH 12B NEMO
Author: bamec66557

VICIOUS MESH 12B NEMO is an open-source language model by bamec66557. Features: 12b LLM, VRAM: 24.5GB, Context: 128K, License: apache-2.0, Instruction-Based, Merged, LLM Explorer Score: 0.22.

Merged Model Arxiv:2306.01708 Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-n... Conversational Endpoints compatible Instruct Mistral Model-index Not-for-all-audiences Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bamec66557/VICIOUS_MESH-12B-NEMO

VICIOUS MESH 12B NEMO Parameters and Internals

LLM Name	VICIOUS MESH 12B NEMO
Repository 🤗	https://huggingface.co/bamec66557/VICIOUS_MESH-12B-NEMO
Base Model(s)	Mistral Nemo Instruct 2407 mistralai/Mistral-Nemo-Instruct-2407
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2025-09-23
Maintainer	bamec66557
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
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the VICIOUS MESH 12B NEMO 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 VICIOUS MESH 12B NEMO

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
...g M Claude Opus High Reasoning	1000K / 24.5 GB	82	3
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

Note: green Score (e.g. "73.2") means that the model is better than bamec66557/VICIOUS_MESH-12B-NEMO.