What are the hardware requirements for Marcoro14 7B Slerp?

Marcoro14 7B Slerp requires approximately 14.5 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 mlabonne, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Marcoro14 7B Slerp perform on standard benchmarks?

Marcoro14 7B Slerp has the following published scores: MMLU 65.11. Compare against reference models on this page or on the LLM Explorer leaderboards.

Marcoro14 7B Slerp by mlabonne — VRAM 14.5GB, 32K context

Name: Marcoro14 7B Slerp
Author: mlabonne

Marcoro14 7B Slerp is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.12, Arc: 69.8, HellaSwag: 87.1, MMLU: 65.1, GSM8K: 70.9.

Merged Model Aidc-ai-business/marcoroni-7b-... Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

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

Marcoro14 7B Slerp Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, commercial applications

Applications:

text generation

Primary Use Cases:

AI2 Reasoning Challenge, HellaSwag, MMLU, TruthfulQA, Winogrande, GSM8k

Additional Notes

This model was evaluated using Nous' benchmark suite, achieving an average score of 57.67%.

Training Details

Methodology:

Merge of AIDC-ai-business/Marcoroni-7B-v3 and EmbeddedLLM/Mistral-7B-Merge-14-v0.1 using SLERP method.

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Marcoro14 7B Slerp
Repository 🤗	https://huggingface.co/mlabonne/Marcoro14-7B-slerp
Merged Model	Yes
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-06-07
Maintainer	mlabonne
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.6 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Marcoro14 7B Slerp 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

Quantized Models of the Marcoro14 7B Slerp

Model	Likes	Downloads	VRAM
...tilled 7B SLERP 8.0bpw H8 EXL2	1	1	7 GB

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 mlabonne/Marcoro14-7B-slerp.