What are the hardware requirements for Boundary Mistral 4x7b MoE?

Boundary Mistral 4x7b MoE requires approximately 48.7 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 Boundary Mistral 4x7b MoE and how large is it?

Boundary Mistral 4x7b MoE is developed by NotAiLOL, 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.

Where can I download or evaluate Boundary Mistral 4x7b MoE?

Boundary Mistral 4x7b MoE is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Boundary Mistral 4x7b MoE by NotAiLOL — VRAM 48.7GB, 32K context

Name: Boundary Mistral 4x7b MoE
Author: NotAiLOL

Boundary Mistral 4x7b MoE is an open-source language model by NotAiLOL. Features: 24.2b LLM, VRAM: 48.7GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.12.

Autotrain compatible Base model:huggingfaceh4/zephy... Base model:merge:huggingfaceh4... Base model:merge:meta-math/met... Base model:merge:mistralai/mis... Base model:merge:teknium/openh... Base model:merge:teknium/openh... Base model:meta-math/metamath-... Base model:mistralai/mistral-7... Base model:teknium/openhermes-... Base model:teknium/openhermes-... Conversational Endpoints compatible Huggingfaceh4/zephyr-7b-beta Instruct Merge Mergekit Meta-math/metamath-mistral-7b Mistral Mistralai/mistral-7b-instruct-... Mixtral Moe Region:us Safetensors Sharded Teknium/openhermes-2.5-mistral... Tensorflow

Model Card on HF 🤗: https://huggingface.co/NotAiLOL/Boundary-mistral-4x7b-MoE

Boundary Mistral 4x7b MoE Parameters and Internals

LLM Name	Boundary Mistral 4x7b MoE
Repository 🤗	https://huggingface.co/NotAiLOL/Boundary-mistral-4x7b-MoE
Base Model(s)	Zephyr 7B Beta mistralai/Mistral-7B-Instruct-v0.2 teknium/OpenHermes-2.5-Mistral-7B MetaMath Mistral 7B HuggingFaceH4/zephyr-7b-beta mistralai/Mistral-7B-Instruct-v0.2 teknium/OpenHermes-2.5-Mistral-7B meta-math/MetaMath-Mistral-7B
Model Size	24.2b
Required VRAM	48.7 GB
Updated	2024-08-10
Maintainer	NotAiLOL
Model Type	mixtral
Instruction-Based	Yes
Model Files	1.9 GB: 1-of-25 1.9 GB: 2-of-25 2.0 GB: 3-of-25 2.0 GB: 4-of-25 1.9 GB: 5-of-25 2.0 GB: 6-of-25 2.0 GB: 7-of-25 1.9 GB: 8-of-25 2.0 GB: 9-of-25 2.0 GB: 10-of-25 2.0 GB: 11-of-25 1.9 GB: 12-of-25 2.0 GB: 13-of-25 2.0 GB: 14-of-25 1.9 GB: 15-of-25 2.0 GB: 16-of-25 2.0 GB: 17-of-25 1.9 GB: 18-of-25 2.0 GB: 19-of-25 2.0 GB: 20-of-25 1.9 GB: 21-of-25 2.0 GB: 22-of-25 2.0 GB: 23-of-25 2.0 GB: 24-of-25 1.5 GB: 25-of-25
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Boundary Mistral 4x7b MoE capabilities

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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 Boundary Mistral 4x7b MoE

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
...erges MoE 4x7b V10 Mixtralv0.3	32K / 48.3 GB	6	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
...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 NotAiLOL/Boundary-mistral-4x7b-MoE.