What are the hardware requirements for Marcoro14 7B Slerp?

Marcoro14 7B Slerp requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Marcoro14 7B Slerp is developed by ayousanz, 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 Marcoro14 7B Slerp?

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

Marcoro14 7B Slerp by ayousanz — VRAM 14.4GB, 32K context

Name: Marcoro14 7B Slerp
Author: ayousanz

Marcoro14 7B Slerp is an open-source language model by ayousanz. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.1.

Merged Model Base model:greennode/greennode... Base model:viethq188/leoscorpi... Endpoints compatible Greennode/greennodelm-7b-v1ole... Mistral Region:us Safetensors Sharded Tensorflow Viethq188/leoscorpius-7b-chat-...

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

Marcoro14 7B Slerp Parameters and Internals

Model Type

merge

Additional Notes

Marcoro14-7B-slerp is a merge of the following models using mergekit: viethq188/LeoScorpius-7B-Chat-DPO and GreenNode/GreenNodeLM-7B-v1olet.

LLM Name	Marcoro14 7B Slerp
Repository 🤗	https://huggingface.co/ayousanz/Marcoro14-7B-slerp
Base Model(s)	LeoScorpius 7B Chat DPO ...de Mini 7B Multilingual V1olet viethq188/LeoScorpius-7B-Chat-DPO GreenNode/GreenNode-mini-7B-multilingual-v1olet
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-05-19
Maintainer	ayousanz
Model Type	mistral
Model Files	1.9 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 1.9 GB: 4-of-8 2.0 GB: 5-of-8 1.9 GB: 6-of-8 2.0 GB: 7-of-8 0.8 GB: 8-of-8
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Marcoro14 7B Slerp capabilities

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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 Marcoro14 7B Slerp

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

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