What are the hardware requirements for Mergekit Passthrough Yqhuxcv GGUF?

Mergekit Passthrough Yqhuxcv GGUF requires approximately 16.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mergekit Passthrough Yqhuxcv GGUF and how large is it?

Mergekit Passthrough Yqhuxcv GGUF is developed by MaziyarPanahi, a model with 70b 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 Yqhuxcv GGUF?

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

Mergekit Passthrough Yqhuxcv GGUF by MaziyarPanahi — VRAM 16.9GB

Name: Mergekit Passthrough Yqhuxcv GGUF
Author: MaziyarPanahi

Mergekit Passthrough Yqhuxcv GGUF is an open-source language model by MaziyarPanahi. Features: 70b LLM, VRAM: 16.9GB, Quantized, LLM Explorer Score: 0.13.

2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Autotrain compatible Base model:aaditya/llama3-open... Base model:mergekit-community/... Base model:quantized:mergekit-... Conversational Endpoints compatible Gguf Llama Merge Mergekit Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/mergekit-passthrough-yqhuxcv-GGUF

Mergekit Passthrough Yqhuxcv GGUF Parameters and Internals

Model Type

text-generation, conversational

Additional Notes

This model supports GGUF format, which is a replacement for GGML, introduced by the llama.cpp team on August 21st, 2023. The model is compatible with various platforms and libraries supporting the GGUF format.

LLM Name	Mergekit Passthrough Yqhuxcv GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/mergekit-passthrough-yqhuxcv-GGUF
Model Name	mergekit-passthrough-yqhuxcv-GGUF
Model Creator	mergekit-community
Base Model(s)	mergekit-community/mergekit-passthrough-yqhuxcv mergekit-community/mergekit-passthrough-yqhuxcv
Model Size	70b
Required VRAM	16.9 GB
Updated	2026-08-01
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	16.9 GB 23.7 GB 21.9 GB 19.7 GB 27.1 GB 25.7 GB 31.8 GB 31.0 GB 36.8 GB 47.7 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the Mergekit Passthrough Yqhuxcv GGUF 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 Passthrough Yqhuxcv GGUF

Best Alternatives	Context / RAM	Downloads	Likes
...us Qwen3 R1 Llama Distill GGUF	0K / 0.8 GB	63	2
KafkaLM 70B German V0.1 GGUF	0K / 25.5 GB	1974	84
CodeLlama 70B Python GGUF	0K / 25.5 GB	1799	45
CodeLlama 70B Instruct GGUF	0K / 25.5 GB	1375	64
Meta Llama 3 70B Instruct GGUF	0K / 26.4 GB	133	4
DAD Model V2 70B Q4	0K / 42.5 GB	13	0
CodeLlama 70B Hf GGUF	0K / 25.5 GB	618	42
Llama 2 70B Guanaco QLoRA GGUF	0K / 29.3 GB	22	0
Swallow 70B Instruct GGUF	0K / 29.4 GB	1495	9
Llama 2 70B Chat GGUF	0K / 29.3 GB	3619	122

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