What are the hardware requirements for Muse Glimmer 30B?

Muse Glimmer 30B requires approximately 59.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Muse Glimmer 30B is developed by meta-models, a model with 30b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Muse Glimmer 30B perform on standard benchmarks?

Muse Glimmer 30B has the following published scores: LMSYS ELO 1426. Compare against reference models on this page or on the LLM Explorer leaderboards.

Muse Glimmer 30B by meta-models — VRAM 59.6GB

Name: Muse Glimmer 30B
Author: meta-models

Muse Glimmer 30B is an open-source language model by meta-models. Features: 30b LLM, VRAM: 59.6GB, License: apache-2.0, LLM Explorer Score: 0.53, ELO: 1426.

Arxiv:2504.13181 Arxiv:2602.06036 Conversational Endpoints compatible Eval-results Image-text-to-text Muse glimmer Region:us Safetensors Sharded Tensorflow

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

Muse Glimmer 30B Benchmarks

LMSys ELO 1426 vs 1272 (so35) 12.1%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Muse Glimmer 30B Parameters and Internals

LLM Name	Muse Glimmer 30B
Repository 🤗	https://huggingface.co/meta-models/Muse-Glimmer-30B
Model Size	30b
Required VRAM	59.6 GB
Updated	2026-08-11
Maintainer	meta-models
Model Type	muse_glimmer
Model Files	50.0 GB: 1-of-2 9.6 GB: 2-of-2
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 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

Quantized Models of the Muse Glimmer 30B

Model	Likes	Downloads	VRAM
Muse Glimmer Q4 MLX	6	5949	15 GB
Muse Glimmer 30B 8bit	2	2935	11 GB
Muse Glimmer 30B AWQ INT4	8	985	24 GB
Muse Glimmer 30B OptiQ 4bit	1	360	19 GB
Muse Glimmer 30B MLX 8bit	1	107	33 GB
...use Glimmer 30B Hermes Agentic	2	37	59 GB
Muse Glimmer 30B AWQ FP8	1	45	34 GB
Muse Glimmer 30B 4bit	11	0	19 GB
Muse Glimmer 30B NVFP4 GPTQ Mm	1	37	23 GB
Muse Glimmer 30B GPTQ INT4	2	17	23 GB

Best Alternatives to Muse Glimmer 30B

Best Alternatives	Context / RAM	Downloads	Likes
Muse Glimmer 30B	0K / 59.6 GB	25869	12
Muse Glimmer 30B FP8 Block	0K / 34.4 GB	19413	9
Muse Glimmer 30B NVFP4	0K / 23.4 GB	7245	16
Muse Glimmer 30B NVFP4 W4A4	0K / 12.1 GB	10907	3
Muse Glimmer 30B	0K / 59.6 GB	2967	0
Muse Glimmer 30B NVFP4	0K / 23.3 GB	1196	6
Muse Glimmer 30B Nvfp4	0K / 11.4 GB	1437	2
Muse Glimmer 30B JANG 6M	0K / 27.1 GB	915	2
...e Glimmer 30B MXFP8 Vision MLX	0K / 35.2 GB	912	1
Muse Glimmer 30B Tq3 G64	0K / 13.5 GB	739	1