What are the hardware requirements for Distilabeled Marcoro14 7B Slerp GGUF?

Distilabeled Marcoro14 7B Slerp GGUF requires approximately 2.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Distilabeled Marcoro14 7B Slerp GGUF and how large is it?

Distilabeled Marcoro14 7B Slerp GGUF is developed by MaziyarPanahi, a model with 7b 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 Distilabeled Marcoro14 7B Slerp GGUF?

Distilabeled Marcoro14 7B Slerp GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Distilabeled Marcoro14 7B Slerp GGUF by MaziyarPanahi — VRAM 2.7GB

Name: Distilabeled Marcoro14 7B Slerp GGUF
Author: MaziyarPanahi

Distilabeled Marcoro14 7B Slerp GGUF is an open-source language model by MaziyarPanahi. Features: 7b LLM, VRAM: 2.7GB, Quantized, LLM Explorer Score: 0.11.

2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Autotrain compatible Base model:argilla/distilabele... Base model:mlabonne/marcoro14-... Base model:quantized:argilla/d... Dataset:argilla/distilabel-int... Distilabel Dpo En Endpoints compatible Gguf Has space Merge Mergekit Mistral Quantized Region:us Rlaif Rlhf Safetensors

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/distilabeled-Marcoro14-7B-slerp-GGUF

Distilabeled Marcoro14 7B Slerp GGUF Parameters and Internals

LLM Name	Distilabeled Marcoro14 7B Slerp GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/distilabeled-Marcoro14-7B-slerp-GGUF
Model Name	distilabeled-Marcoro14-7B-slerp-GGUF
Model Creator	argilla
Base Model(s)	...istilabeled Marcoro14 7B Slerp argilla/distilabeled-Marcoro14-7B-slerp
Model Size	7b
Required VRAM	2.7 GB
Updated	2026-07-25
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	2.7 GB 3.8 GB 3.5 GB 3.2 GB 4.4 GB 4.1 GB 5.1 GB 5.0 GB 5.9 GB 7.7 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the Distilabeled Marcoro14 7B Slerp 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 Distilabeled Marcoro14 7B Slerp GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Pixel	8K / 4.4 GB	17	0
Qwen2 7B Alpacha Q8 0	0K / 9.1 GB	23	0
...ral 7B Instruct V0.2 Llamafile	0K / 14.5 GB	8850	25
Conversely Mistral 7B	0K / 0.2 GB	132	0
Mistral 7B Instruct V0.3 GGUF	0K / 1.6 GB	91691	147
CleverBoi 7B V2	0K / 0.1 GB	586	0
WizardLM 2 7B GGUF	0K / 2.7 GB	93547	83
Qwen2 7B Instruct GGUF	0K / 1.9 GB	56414	10
...hemeng Qwen Math 7b 24 1 100 1	0K / 15.2 GB	25	0
Mistral 7B Instruct V0.2 GGUF	0K / 3.1 GB	70243	511

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/distilabeled-Marcoro14-7B-slerp-GGUF.