What are the hardware requirements for Merged Model MoE?

Merged Model MoE requires approximately 53.3 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 Merged Model MoE and how large is it?

Merged Model MoE is developed by EthanLiu1991, 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 Merged Model MoE?

Merged Model MoE is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Merged Model MoE by EthanLiu1991 — VRAM 53.3GB, 32K context

Name: Merged Model MoE
Author: EthanLiu1991

Merged Model MoE is an open-source language model by EthanLiu1991. Features: 7b LLM, VRAM: 53.3GB, Context: 32K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.13.

Merged Model Conversational Endpoints compatible Mixtral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/EthanLiu1991/Merged_model_MoE

Merged Model MoE Parameters and Internals

Model Type

text-generation

Additional Notes

The model is designed for tasks involving specific prompts associated with the source models.

Input Output

Input Format:

Chat template with specific prompts.

Accepted Modalities:

text

Output Format:

Text generation outputs text

LLM Name	Merged Model MoE
Repository 🤗	https://huggingface.co/EthanLiu1991/Merged_model_MoE
Merged Model	Yes
Model Size	7b
Required VRAM	53.3 GB
Updated	2026-07-26
Maintainer	EthanLiu1991
Model Type	mixtral
Model Files	1.9 GB: 1-of-13 1.9 GB: 1-of-15 2.0 GB: 2-of-13 1.9 GB: 2-of-15 2.0 GB: 3-of-13 1.9 GB: 3-of-15 2.0 GB: 4-of-13 1.9 GB: 4-of-15 2.0 GB: 5-of-13 1.9 GB: 5-of-15 2.0 GB: 6-of-13 1.9 GB: 6-of-15 2.0 GB: 7-of-13 1.9 GB: 7-of-15 2.0 GB: 8-of-13 1.9 GB: 8-of-15 2.0 GB: 9-of-13 1.9 GB: 9-of-15 2.0 GB: 10-of-13 1.9 GB: 10-of-15 2.0 GB: 11-of-13 1.9 GB: 11-of-15 2.0 GB: 12-of-13 1.9 GB: 12-of-15 1.9 GB: 13-of-13 1.9 GB: 13-of-15 2.0 GB: 14-of-15 0.8 GB: 15-of-15
Model Architecture	MixtralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Merged Model MoE 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 Merged Model MoE

Best Alternatives	Context / RAM	Downloads	Likes
Multimaster 7B V6	32K / 142.5 GB	8108	2
Mini Mixtral V0.2	32K / 25.8 GB	3923	4
MultiverseBuddy 15B MoE	32K / 25.8 GB	9	0
Lumina 2	32K / 37.1 GB	6	0
OpenMistral MoE	32K / 48.3 GB	1218	0
RogerWizard 12B MoE	32K / 25.8 GB	4	1
Rawr	32K / 93.5 GB	1302	0
StarlingMaths 12B MoE	32K / 25.8 GB	5	0
Lumina 3	32K / 37.1 GB	45	0
MultiverseMath 12B MoE	32K / 25.8 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than EthanLiu1991/Merged_model_MoE.