What are the hardware requirements for Muse Glimmer 30B GPTQ INT4?

Muse Glimmer 30B GPTQ INT4 requires approximately 23.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Muse Glimmer 30B GPTQ INT4 and how large is it?

Muse Glimmer 30B GPTQ INT4 is developed by abhishekchohan, 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 GPTQ INT4 perform on standard benchmarks?

Muse Glimmer 30B GPTQ INT4 has the following published scores: LMSYS ELO 1426. Compare against reference models on this page or on the LLM Explorer leaderboards.

Muse Glimmer 30B GPTQ INT4 by abhishekchohan — VRAM 23.9GB

Name: Muse Glimmer 30B GPTQ INT4
Author: abhishekchohan

Muse Glimmer 30B GPTQ INT4 is an open-source language model by abhishekchohan. Features: 30b LLM, VRAM: 23.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.44, ELO: 1426.

Base model:meta-models/muse-gl... Base model:quantized:meta-mode... Compressed-tensors Conversational Endpoints compatible Gptq Image-text-to-text Imatrix Int4 Muse-glimmer Muse glimmer Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/abhishekchohan/Muse-Glimmer-30B-GPTQ-INT4

Muse Glimmer 30B GPTQ INT4 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 GPTQ INT4 Parameters and Internals

LLM Name	Muse Glimmer 30B GPTQ INT4
Repository 🤗	https://huggingface.co/abhishekchohan/Muse-Glimmer-30B-GPTQ-INT4
Base Model(s)	Muse Glimmer 30B meta-models/Muse-Glimmer-30B
Model Size	30b
Required VRAM	23.9 GB
Updated	2026-08-13
Maintainer	abhishekchohan
Model Type	muse_glimmer
Model Files	3.7 GB: 1-of-7 4.0 GB: 2-of-7 4.0 GB: 3-of-7 4.0 GB: 4-of-7 4.0 GB: 5-of-7 1.5 GB: 6-of-7 2.7 GB: 7-of-7
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MuseGlimmerForConditionalGeneration
License	apache-2.0
Model Max Length	131072
Transformers Version	5.15.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|finetune_right_pad\|>

Rank the Muse Glimmer 30B GPTQ INT4 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 GPTQ INT4

Best Alternatives	Context / RAM	Downloads	Likes
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	15	1
Muse Glimmer 30B	0K / 59.6 GB	0	1052
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	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

Note: green Score (e.g. "73.2") means that the model is better than abhishekchohan/Muse-Glimmer-30B-GPTQ-INT4.