What are the hardware requirements for MixtureofMerges MoE 4x7b V10 Mixtralv0.3?

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 requires approximately 48.3 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 MixtureofMerges MoE 4x7b V10 Mixtralv0.3 and how large is it?

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 is developed by jsfs11, a model with 24.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does MixtureofMerges MoE 4x7b V10 Mixtralv0.3 perform on standard benchmarks?

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 has the following published scores: MMLU 63.38. Compare against reference models on this page or on the LLM Explorer leaderboards.

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 by jsfs11 — VRAM 48.3GB, 32K context

Name: MixtureofMerges MoE 4x7b V10 Mixtralv0.3
Author: jsfs11

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 is an open-source language model by jsfs11. Features: 24.2b LLM, VRAM: 48.3GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.13, Arc: 66.4, HellaSwag: 84.9, MMLU: 63.4, GSM8K: 57.5.

Base model:kukedlc/neuralsynth... Base model:merge:kukedlc/neura... Base model:merge:mistralai/mis... Base model:merge:mlabonne/alph... Base model:merge:s3nh/severusw... Base model:mistralai/mistral-7... Base model:mlabonne/alphamonar... Base model:s3nh/severuswestlak... Conversational Endpoints compatible Frankenmoe Instruct Kukedlc/neuralsynthesis-7b-v0.... Lazymergekit Merge Mergekit Mistralai/mistral-7b-instruct-... Mixtral Mlabonne/alphamonarch-7b Moe Region:us S3nh/severuswestlake-7b-dpo Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/jsfs11/MixtureofMerges-MoE-4x7b-v10-mixtralv0.3

MixtureofMerges MoE 4x7b V10 Mixtralv0.3 Parameters and Internals

Model Type

mixture of experts (MoE)

LLM Name	MixtureofMerges MoE 4x7b V10 Mixtralv0.3
Repository 🤗	https://huggingface.co/jsfs11/MixtureofMerges-MoE-4x7b-v10-mixtralv0.3
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.3 Kukedlc/NeuralSynthesis-7B-v0.1 AlphaMonarch 7B SeverusWestLake 7B DPO mistralai/Mistral-7B-Instruct-v0.3 Kukedlc/NeuralSynthesis-7B-v0.1 mlabonne/AlphaMonarch-7B s3nh/SeverusWestLake-7B-DPO
Model Size	24.2b
Required VRAM	48.3 GB
Updated	2026-07-01
Maintainer	jsfs11
Model Type	mixtral
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-5 10.0 GB: 2-of-5 10.0 GB: 3-of-5 10.0 GB: 4-of-5 8.4 GB: 5-of-5
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.1
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the MixtureofMerges MoE 4x7b V10 Mixtralv0.3 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 MixtureofMerges MoE 4x7b V10 Mixtralv0.3

Best Alternatives	Context / RAM	Downloads	Likes
Proto Athena 4x7B	32K / 48.4 GB	5	0
Proto Athena V0.2 4x7B	32K / 48.4 GB	8	0
Sixtyoneeighty 4x7B V1	32K / 48.3 GB	62	0
MixtureofMerges MoE 4x7bRP V11	32K / 48.3 GB	4	1
West Ramen 7Bx4	32K / 48.7 GB	53	0
Eclipse Mistral 4x7b	32K / 48.5 GB	16	1
MoE Merging	32K / 48.3 GB	70	0
Boundary Mistral 4x7b MoE	32K / 48.7 GB	117	1
...tral Fusion 4x7B Instruct V0.1	32K / 48.5 GB	8	18
... Extraction 4x7B Instruct V0.1	32K / 48.5 GB	4	5

Note: green Score (e.g. "73.2") means that the model is better than jsfs11/MixtureofMerges-MoE-4x7b-v10-mixtralv0.3.