What are the hardware requirements for Muse Glimmer 30B JANG 4M?

Muse Glimmer 30B JANG 4M requires approximately 21 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Muse Glimmer 30B JANG 4M and how large is it?

Muse Glimmer 30B JANG 4M is developed by OsaurusAI, a model with 30b 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 Glimmer 30B JANG 4M?

Muse Glimmer 30B JANG 4M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Muse Glimmer 30B JANG 4M by OsaurusAI — VRAM 21GB

Name: Muse Glimmer 30B JANG 4M
Author: OsaurusAI

Muse Glimmer 30B JANG 4M is an open-source language model by OsaurusAI. Features: 30b LLM, VRAM: 21GB, License: apache-2.0, LLM Explorer Score: 0.32.

Apple-silicon Atem Base model:meta-models/muse-gl... Base model:quantized:meta-mode... Conversational En Image-text-to-text Jang Jang-4m Mlx Muse-glimmer Muse glimmer Quantized Reasoning Region:us Safetensors Sharded Tensorflow Tool-use Vision Vision-language

Model Card on HF 🤗: https://huggingface.co/OsaurusAI/Muse-Glimmer-30B-JANG_4M

Muse Glimmer 30B JANG 4M Parameters and Internals

LLM Name	Muse Glimmer 30B JANG 4M
Repository 🤗	https://huggingface.co/OsaurusAI/Muse-Glimmer-30B-JANG_4M
Base Model(s)	Muse Glimmer 30B meta-models/Muse-Glimmer-30B
Model Size	30b
Required VRAM	21 GB
Updated	2026-08-13
Maintainer	OsaurusAI
Model Type	muse_glimmer
Model Files	0.8 GB: 1-of-32 0.5 GB: 2-of-32 0.5 GB: 3-of-32 0.5 GB: 4-of-32 0.5 GB: 5-of-32 0.5 GB: 6-of-32 0.5 GB: 7-of-32 0.5 GB: 8-of-32 0.5 GB: 9-of-32 0.5 GB: 10-of-32 0.5 GB: 11-of-32 0.5 GB: 12-of-32 0.5 GB: 13-of-32 0.5 GB: 14-of-32 0.5 GB: 15-of-32 0.5 GB: 16-of-32 0.5 GB: 17-of-32 0.5 GB: 18-of-32 0.5 GB: 19-of-32 0.5 GB: 20-of-32 0.5 GB: 21-of-32 0.5 GB: 22-of-32 0.5 GB: 23-of-32 0.5 GB: 24-of-32 0.5 GB: 25-of-32 0.5 GB: 26-of-32 1.8 GB: 27-of-32 0.5 GB: 28-of-32 0.5 GB: 29-of-32 0.5 GB: 30-of-32 0.5 GB: 31-of-32 3.9 GB: 32-of-32
Supported Languages	en
Model Architecture	MuseGlimmerForConditionalGeneration
License	apache-2.0
Model Max Length	131072
Transformers Version	5.15.0.dev0
Tokenizer Class	TokenizersBackend
Padding Token	<\|finetune_right_pad\|>

Rank the Muse Glimmer 30B JANG 4M 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 Muse Glimmer 30B JANG 4M

Best Alternatives	Context / RAM	Downloads	Likes
Muse Glimmer 30B	0K / 59.6 GB	0	1052
Muse Glimmer 30B	0K / 59.6 GB	25869	12
Muse Glimmer 30B FP8 Block	0K / 34.4 GB	19413	9
Muse Glimmer 30B NVFP4 W4A4	0K / 12.1 GB	10907	3
Muse Glimmer 30B NVFP4	0K / 23.3 GB	1196	6
Muse Glimmer 30B JANG 6M	0K / 27.1 GB	915	2
Muse Glimmer 30B NVFP4	0K / 23.4 GB	566	2
...e Glimmer 30B MXFP8 Vision MLX	0K / 35.2 GB	912	1
... Glimmer 30B Abliterated NVFP4	0K / 29.7 GB	166	3
Muse Glimmer 30B Tq3 G64	0K / 13.5 GB	739	1

Note: green Score (e.g. "73.2") means that the model is better than OsaurusAI/Muse-Glimmer-30B-JANG_4M.