What are the hardware requirements for Mewthree 7B?

Mewthree 7B 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 Mewthree 7B and how large is it?

Mewthree 7B is developed by jeiku, 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 Mewthree 7B perform on standard benchmarks?

Mewthree 7B has the following published scores: MMLU 62.56. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mewthree 7B by jeiku — VRAM 14.4GB, 32K context

Name: Mewthree 7B
Author: jeiku

Mewthree 7B is an open-source language model by jeiku. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: other, Merged, LLM Explorer Score: 0.14, Arc: 65.8, HellaSwag: 85.7, MMLU: 62.6, GSM8K: 23.9.

Merged Model Base model:finetune:krisbianto... Base model:krisbiantoro/mistra... Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/jeiku/Mewthree_7B

Mewthree 7B Benchmarks

ARC: 65.78 vs 96.7 (so35)^-32%

HellaSwag: 85.74 vs 95.3 (gpt4)^-10%

MMLU: 62.56 vs 88.3 (so35)^-29.2%

GSM8K: 23.88 vs 96.4 (so35)^-75.2%

LLME Score: 0.13553

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

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Mewthree 7B Parameters and Internals

Additional Notes

Draws upon the Prodigy lineage with some elements of robotics, memerboard essence, and BioMistral for anatomy. A DPO LoRA was applied on top, and it handles markdown well, with a focus on RP (role-play).

LLM Name	Mewthree 7B
Repository 🤗	https://huggingface.co/jeiku/Mewthree_7B
Base Model(s)	Krisbiantoro/mistral7b_dpo_en Krisbiantoro/mistral7b_dpo_en
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-05-25
Maintainer	jeiku
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.1
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Quantized Models of the Mewthree 7B

Model	Likes	Downloads	VRAM
Mewthree 7B AWQ	1	3	4 GB

Best Alternatives to Mewthree 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	254	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8623	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	24	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	8131	17
Hebrew Mistral 7B 200K	256K / 30 GB	1378	15
Astral 256K 7B V2	250K / 14.4 GB	5	0
Astral 256K 7B	250K / 14.4 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than jeiku/Mewthree_7B.

Rank the Mewthree 7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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

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Mewthree 7B by jeiku