What are the hardware requirements for L3.1 MoE 2x8B V0.2?

L3.1 MoE 2x8B V0.2 requires approximately 27.3 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed L3.1 MoE 2x8B V0.2 and how large is it?

L3.1 MoE 2x8B V0.2 is developed by moeru-ai, a model with 13.7b 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 L3.1 MoE 2x8B V0.2?

L3.1 MoE 2x8B V0.2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

L3.1 MoE 2x8B V0.2 by moeru-ai — VRAM 27.3GB, 128K context

Name: L3.1 MoE 2x8B V0.2
Author: moeru-ai

L3.1 MoE 2x8B V0.2 is an open-source language model by moeru-ai. Features: 13.7b LLM, VRAM: 27.3GB, Context: 128K, License: llama3.1, MoE, LLM Explorer Score: 0.23.

Base model:arliai/llama-3.1-8b... Base model:joseph717171/llama-... Base model:merge:arliai/llama-... Base model:merge:joseph717171/... Conversational Endpoints compatible Frankenmoe Merge Mergekit Mixtral Model-index Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/moeru-ai/L3.1-Moe-2x8B-v0.2

L3.1 MoE 2x8B V0.2 Parameters and Internals

LLM Name	L3.1 MoE 2x8B V0.2
Repository 🤗	https://huggingface.co/moeru-ai/L3.1-Moe-2x8B-v0.2
Base Model(s)	Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2 Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2
Model Size	13.7b
Required VRAM	27.3 GB
Updated	2026-07-27
Maintainer	moeru-ai
Model Type	mixtral
Model Files	5.0 GB: 1-of-6 4.9 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 4.9 GB: 5-of-6 2.5 GB: 6-of-6
Model Architecture	MixtralForCausalLM
License	llama3.1
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|begin_of_text\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the L3.1 MoE 2x8B V0.2 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

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