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Muse-Glimmer-30B-abliterated

Muse-Glimmer-30B-abliterated is a refusal-ablated variant of meta-models/Muse-Glimmer-30B, published on Hugging Face by nramanan. It is 30B parameters, 48GB VRAM class class and apache-2.0 licence. It is distributed across 34 repositories in GGUF, Full precision, GGUF (imatrix) and Transformers formats, totalling 48.9K downloads.

Abliteration (directional ablation)30BOther25B – 50B↓ 48,860♥ 56

Specification

Model name
Muse-Glimmer-30B-abliterated
Publisher
nramanan
Parameters
30B
VRAM required
~19 GB at Q4_K_M, 4k context (estimated) — runs on 24 GB cards
Hardware class
25B – 50B — 48GB VRAM class
Licence
apache-2.0
Task
Image text to text
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF, Full precision, GGUF (imatrix), Transformers, MLX
First indexed
10 Aug 2026
Last updated
20 Oct 2026

Ablation technique

How Muse-Glimmer-30B-abliterated was modified, and what that implies.

Abliteration (directional ablation)

The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download The-freezer/Muse-Glimmer-30B-Abliterated-GGUF --local-dir ./muse-glimmer-30b-abliterated
llama-cli -m ./muse-glimmer-30b-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "nramanan/Muse-Glimmer-30B-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve nramanan/Muse-Glimmer-30B-abliterated --trust-remote-code

Downloads and variants (33)

Every published repository of Muse-Glimmer-30B-abliterated, including quantised re-releases by other authors.

RepositoryFormatDownloads
The-freezer/Muse-Glimmer-30B-Abliterated-GGUFGGUF38.6K
mradermacher/Muse-Glimmer-30B-Abliterated-BF16-i1-GGUFGGUF (imatrix)3.3K
cvgro/Muse-Glimmer-30B-Abliterated-GGUFGGUF1.3K
mradermacher/Muse-Glimmer-30B-Abliterated-GGUFGGUF968
mradermacher/Muse-Glimmer-30B-Abliterated-i1-GGUFGGUF (imatrix)885
mradermacher/Muse-Glimmer-30B-Abliterated-BF16-GGUFGGUF646
saracen9/muse-glimmer-30b-abliterated-GGUFGGUF343
nramanan/Muse-Glimmer-30B-abliteratedsourceTransformers315
0xSojalSec/Muse-Glimmer-30B-Abliterated-GGUFGGUF244
mlasli/Muse-Glimmer-30B-Abliterated-Q4_K_M-GGUFGGUF217
kmnstudio101/Muse-Glimmer-30B-AbliteratedTransformers212
Ishowbackup/Muse-Glimmer-30B-Abliterated-GGUFGGUF211
mlasli/Muse-Glimmer-30B-Abliterated-Q8_0-GGUFGGUF167
Ishowbackup/Muse-Glimmer-30B-Abliterated-MLX-4bitMLX167
jorkle/Muse-Glimmer-30B-Abliterated-GGUFGGUF139
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-q6MLX134
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-q8MLX131
mlasli/Muse-Glimmer-30B-Abliterated-Q6_K-GGUFGGUF120
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-q4MLX86
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-mxfp4MLX80
mlasli/Muse-Glimmer-30B-Abliterated-FP16-GGUFGGUF76
Ishowbackup/Muse-Glimmer-30B-Abliterated-MLX-4bit-AWQMLX60
Ishowbackup/Muse-Glimmer-30B-Abliterated-MLX-3bitMLX51
jorkle/Muse-Glimmer-30B-AbliteratedTransformers48
Ishowbackup/Muse-Glimmer-30B-Abliterated-MLX-3bit-AWQMLX48
Ishowbackup/Muse-Glimmer-30B-Abliterated-MLX-NVFP4MLX39
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-q3MLX37
shoemoney/Muse-Glimmer-30B-Abliterated-MLX-q5MLX36
mlasli/Muse-Glimmer-30B-Abliterated-BF16Full precision29
dudeman2512/Muse-Glimmer-30B-abliteratedTransformers26
Plus 3 further repositories with fewer downloads, all counted in the totals above.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • Muse-Glimmer-30B-abliterated will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • Capability is inherited from meta-models/Muse-Glimmer-30B, not added by ablation — at 30B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • Declared licence is apache-2.0, but the terms that bind you are meta-models/Muse-Glimmer-30B’s — a re-release cannot grant more than its parent.
  • The source repository is gated, so downloading requires accepting the publisher’s terms.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for Muse-Glimmer-30B-abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with nramanan, and does not independently verify publisher claims. See responsible use.