What are the hardware requirements for Muse Glimmer 30B MLX 8bit?

Muse Glimmer 30B MLX 8bit requires approximately 33.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Muse Glimmer 30B MLX 8bit and how large is it?

Muse Glimmer 30B MLX 8bit is developed by Vontra, 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 MLX 8bit perform on standard benchmarks?

Muse Glimmer 30B MLX 8bit has the following published scores: LMSYS ELO 1426. Compare against reference models on this page or on the LLM Explorer leaderboards.

Muse Glimmer 30B MLX 8bit by Vontra — VRAM 33.4GB

Name: Muse Glimmer 30B MLX 8bit
Author: Vontra

Muse Glimmer 30B MLX 8bit is an open-source language model by Vontra. Features: 30b LLM, VRAM: 33.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.43, ELO: 1426.

8-bit 8bit Apple-silicon Base model:meta-models/muse-gl... Base model:quantized:meta-mode... Conversational En Image-text-to-text Mlx Mlx-vlm Multimodal Muse-glimmer Muse glimmer Omlx Quantized Region:us Safetensors Sharded Tensorflow Vision Vision-language

Model Card on HF 🤗: https://huggingface.co/Vontra/Muse-Glimmer-30B-MLX-8bit

Muse Glimmer 30B MLX 8bit 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 MLX 8bit Parameters and Internals

LLM Name	Muse Glimmer 30B MLX 8bit
Repository 🤗	https://huggingface.co/Vontra/Muse-Glimmer-30B-MLX-8bit
Base Model(s)	Muse Glimmer 30B meta-models/Muse-Glimmer-30B
Model Size	30b
Required VRAM	33.4 GB
Updated	2026-08-17
Maintainer	Vontra
Model Type	muse_glimmer
Model Files	5.3 GB: 1-of-7 5.3 GB: 2-of-7 5.3 GB: 3-of-7 5.3 GB: 4-of-7 5.3 GB: 5-of-7 5.4 GB: 6-of-7 1.5 GB: 7-of-7
Supported Languages	en
Quantization Type	8bit
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 MLX 8bit 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 MLX 8bit

Best Alternatives	Context / RAM	Downloads	Likes
Muse Glimmer Q4 MLX	128K / 15.7 GB	5949	6
Muse Glimmer 30B OptiQ 4bit	0K / 19.9 GB	360	1
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	605	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 NVFP4 GPTQ Mm	0K / 23.4 GB	37	1
Muse Glimmer 30B AWQ FP8	0K / 34.5 GB	45	1

Note: green Score (e.g. "73.2") means that the model is better than Vontra/Muse-Glimmer-30B-MLX-8bit.