What are the hardware requirements for Mergekit Model Stock Vkhniqh?

Mergekit Model Stock Vkhniqh requires approximately 24.5 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 Mergekit Model Stock Vkhniqh and how large is it?

Mergekit Model Stock Vkhniqh is developed by mergekit-community, a model with 12.2b 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 Mergekit Model Stock Vkhniqh?

Mergekit Model Stock Vkhniqh is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mergekit Model Stock Vkhniqh by mergekit-community — VRAM 24.5GB, 1000K context

Name: Mergekit Model Stock Vkhniqh
Author: mergekit-community

Mergekit Model Stock Vkhniqh is an open-source language model by mergekit-community. Features: 12.2b LLM, VRAM: 24.5GB, Context: 1000K, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2403.19522 Base model:szilviab/magnum dar... Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mergekit-community/mergekit-model_stock-vkhniqh

Mergekit Model Stock Vkhniqh Parameters and Internals

LLM Name	Mergekit Model Stock Vkhniqh
Repository 🤗	https://huggingface.co/mergekit-community/mergekit-model_stock-vkhniqh
Base Model(s)	Mergekit Model Stock Rxtwhlc Magnum Dark Madness 12b Mergekit Slerp Qtidaqf mergekit-community/mergekit-model_stock-rxtwhlc SzilviaB/Magnum_Dark_Madness_12b mergekit-community/mergekit-slerp-qtidaqf
Merged Model	Yes
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2026-08-07
Maintainer	mergekit-community
Model Type	mistral
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
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.49.0
Tokenizer Class	PreTrainedTokenizer
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mergekit Model Stock Vkhniqh 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 Mergekit Model Stock Vkhniqh

Best Alternatives	Context / RAM	Downloads	Likes
...aptain Eris Violet GRPO V0.420	1000K / 24.5 GB	23	24
...istral Nemo Instruct 2407 MPOA	1000K / 24.5 GB	37	3
...ish Mistral Nemo Instruct 2407	1000K / 24.5 GB	77	2
Mistral Nemo Kurdish	1000K / 24.5 GB	37	3
Violet Twilight V0.2	1000K / 24.5 GB	66	49
Tess Embed Fix Maybe	1000K / 24.5 GB	13	0
Funny Nemo Embedding Testing	1000K / 24.5 GB	5	1
12BTRU	1000K / 24.5 GB	21	0
Another Strange Nemo Model	1000K / 24.5 GB	6	0
A Strange Nemo Model	1000K / 24.5 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than mergekit-community/mergekit-model_stock-vkhniqh.