What are the hardware requirements for Mayonnaise 4in1 02?

Mayonnaise 4in1 02 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 Mayonnaise 4in1 02 and how large is it?

Mayonnaise 4in1 02 is developed by kaitchup, a model with 7.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mayonnaise 4in1 02 perform on standard benchmarks?

Mayonnaise 4in1 02 has the following published scores: MMLU 64.76. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mayonnaise 4in1 02 by kaitchup — VRAM 14.4GB, 32K context

Name: Mayonnaise 4in1 02
Author: kaitchup

Mayonnaise 4in1 02 is an open-source language model by kaitchup. Features: 7.2b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11, Arc: 73, HellaSwag: 88.3, MMLU: 64.8, GSM8K: 70.

En Endpoints compatible Gguf Merge Mistral Model-index Q4 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/kaitchup/Mayonnaise-4in1-02

Mayonnaise 4in1 02 Parameters and Internals

Model Type

Causal

Additional Notes

The model is a mixture of experts blend created using mergekit with the configuration detailed in the article 'The Mayonnaise: Rank First on the Open LLM Leaderboard with TIES-Merging.'

Supported Languages

English (fluent)

LLM Name	Mayonnaise 4in1 02
Repository 🤗	https://huggingface.co/kaitchup/Mayonnaise-4in1-02
Base Model(s)	Mayonnaise 4in1 03 kaitchup/Mayonnaise-4in1-03
Model Size	7.2b
Required VRAM	14.4 GB
Updated	2026-07-22
Maintainer	kaitchup
Model Type	mistral
Model Files	14.5 GB 4.1 GB 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mayonnaise 4in1 02 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 Mayonnaise 4in1 02

Best Alternatives	Context / RAM	Downloads	Likes
Spydaz Web AGI DeepThink	128K / 14.4 GB	14	1
...daz Web AI Pre Train Align 004	128K / 14.4 GB	28	0
Zion Alpha	32K / 14.4 GB	57	4
LCARS AI 001	32K / 14.4 GB	14	4
Mixtral Quantized	32K / 14.4 GB	6	0
Zsql En Postgres	32K / 14.4 GB	64	5
MHENNlitv3	32K / 28.9 GB	12	0
MHENNlitv2	32K / 28.9 GB	17	0
MHENNcodemathv2	32K / 28.9 GB	10	0
MHENNcodemath	32K / 28.9 GB	17	0

Note: green Score (e.g. "73.2") means that the model is better than kaitchup/Mayonnaise-4in1-02.