What are the hardware requirements for Muse Glimmer 30B OptiQ 4bit?

Muse Glimmer 30B OptiQ 4bit requires approximately 19.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Muse Glimmer 30B OptiQ 4bit and how large is it?

Muse Glimmer 30B OptiQ 4bit is developed by mlx-community, 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 OptiQ 4bit perform on standard benchmarks?

Muse Glimmer 30B OptiQ 4bit has the following published scores: LMSYS ELO 1426. Compare against reference models on this page or on the LLM Explorer leaderboards.

Muse Glimmer 30B OptiQ 4bit by mlx-community — VRAM 19.9GB

Name: Muse Glimmer 30B OptiQ 4bit
Author: mlx-community

Muse Glimmer 30B OptiQ 4bit is an open-source language model by mlx-community. Features: 30b LLM, VRAM: 19.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.46, ELO: 1426.

4-bit 4bit Apple-silicon Base model:meta-models/muse-gl... Base model:quantized:meta-mode... Conversational Image-text-to-text Mixed-precision Mlx Multimodal Muse-glimmer Muse glimmer Optiq Quantized Reasoning Region:us Safetensors Sharded Tensorflow Vision Vision-language-model

Model Card on HF 🤗: https://huggingface.co/mlx-community/Muse-Glimmer-30B-OptiQ-4bit

Muse Glimmer 30B OptiQ 4bit 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 OptiQ 4bit Parameters and Internals

LLM Name	Muse Glimmer 30B OptiQ 4bit
Repository 🤗	https://huggingface.co/mlx-community/Muse-Glimmer-30B-OptiQ-4bit
Base Model(s)	Muse Glimmer 30B meta-models/Muse-Glimmer-30B
Model Size	30b
Required VRAM	19.9 GB
Updated	2026-08-15
Maintainer	mlx-community
Model Type	muse_glimmer
Model Files	5.3 GB: 1-of-4 5.3 GB: 2-of-4 5.3 GB: 3-of-4 4.0 GB: 4-of-4
Quantization Type	4bit
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 OptiQ 4bit 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 OptiQ 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Muse Glimmer Q4 MLX	128K / 15.7 GB	5949	6
Muse Glimmer 30B 4bit	0K / 19.4 GB	0	11
...e Glimmer 30B Unsloth Bnb 4bit	0K / 22.2 GB	0	7
...immer 30B Abliterated MLX 6bit	0K / 26.4 GB	291	1
Muse Glimmer 30B	0K / 59.6 GB	0	1052
Muse Glimmer 30B	0K / 59.6 GB	25869	12
Muse Glimmer 30B AWQ INT4	0K / 24.1 GB	985	8
Muse Glimmer 30B AWQ FP8	0K / 34.5 GB	45	1
Muse Glimmer 30B GPTQ INT4	0K / 23.9 GB	17	2
Muse Glimmer 30B FP8 Block	0K / 34.4 GB	19413	9

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Muse-Glimmer-30B-OptiQ-4bit.