What are the hardware requirements for Muse 2 350M?

Muse 2 350M requires approximately 1.4 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 Muse 2 350M and how large is it?

Muse 2 350M is developed by Muse-research, a model with 350m 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 Muse 2 350M?

Muse 2 350M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Muse 2 350M by Muse-research — VRAM 1.4GB, 32K context

Name: Muse 2 350M
Rating: 2.88 (8 reviews)
Author: Muse-research

Muse 2 350M is an open-source language model by Muse-research. Features: 350m LLM, VRAM: 1.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.25.

En Eval-results Grouped-query-attention Long-context Muse-research Muse nova transformer Pytorch Reasoning Region:us Safetensors Science

Model Card on HF 🤗: https://huggingface.co/Muse-research/Muse-2-350M

Muse 2 350M Parameters and Internals

LLM Name	Muse 2 350M
Repository 🤗	https://huggingface.co/Muse-research/Muse-2-350M
Model Size	350m
Required VRAM	1.4 GB
Updated	2026-08-08
Maintainer	Muse-research
Model Type	muse_nova_transformer
Model Files	1.4 GB
Supported Languages	en
Model Architecture	MuseNovaForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	TokenizersBackend
Padding Token	<\|pad\|>
Vocabulary Size	32768

Rank the Muse 2 350M 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