What are the hardware requirements for Mergekit Passthrough Yhjqgnd?

Mergekit Passthrough Yhjqgnd requires approximately 44.2 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 Mergekit Passthrough Yhjqgnd and how large is it?

Mergekit Passthrough Yhjqgnd is developed by mergekit-community, 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 Mergekit Passthrough Yhjqgnd?

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

Mergekit Passthrough Yhjqgnd by mergekit-community — VRAM 44.2GB, 128K context

Name: Mergekit Passthrough Yhjqgnd
Author: mergekit-community

Mergekit Passthrough Yhjqgnd is an open-source language model by mergekit-community. Features: 12b LLM, VRAM: 44.2GB, Context: 128K, Merged, LLM Explorer Score: 0.17.

Merged Model Base model:delta-vector/rei-v2... Base model:finetune:delta-vect... Conversational Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mergekit-community/mergekit-passthrough-yhjqgnd

Mergekit Passthrough Yhjqgnd Parameters and Internals

LLM Name	Mergekit Passthrough Yhjqgnd
Repository 🤗	https://huggingface.co/mergekit-community/mergekit-passthrough-yhjqgnd
Base Model(s)	Rei V2 12B Delta-Vector/Rei-V2-12B
Merged Model	Yes
Model Size	12b
Required VRAM	44.2 GB
Updated	2026-08-03
Maintainer	mergekit-community
Model Type	mistral
Model Files	4.9 GB: 1-of-9 5.0 GB: 2-of-9 4.9 GB: 3-of-9 4.9 GB: 4-of-9 4.9 GB: 5-of-9 4.9 GB: 6-of-9 4.9 GB: 7-of-9 4.9 GB: 8-of-9 4.9 GB: 9-of-9
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 Mergekit Passthrough Yhjqgnd 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

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