← back to catalog · registered 2026-08-22 13:56

mradermacher/Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2-GGUF

mradermacher Nemotron 70B GGUF second-order 131K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FLlama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2-GGUF"
Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 909
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='Nexesenex/Llama_3.x_70b_Nemotron-L3.3_abliterated_fusion_v2' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
909
223 last 30d - stable
Likes
0
Model age
17mo ago
created 2025-04-20
Downloads over time
Now943→from113↑735%
723907081K113 on Apr 16, 2025943 on Oct 11943 on Oct 10Apr '25Jul '25Oct '25JanAprJulOct
Apr 16, 2025 → Oct 11 · 117 snapshots · spans 543 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K
Tags
transformers gguf mergekit merge en base_model:Nexesenex/Llama_3.x_70b_Nemotron-L3.3_abliterated_fusion_v2 base_model:quantized:Nexesenex/Llama_3.x_70b_Nemotron-L3.3_abliterated_fusion_v2 endpoints_compatible region:us conversational

Related

Total size
325 GB
Files
15
Quantizations
6
Registered
2026-08-22 13:56
Last updated on HF
2025-07-31 06:05

Files by quantization

Q5_K 2 files 91.8 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q5_K_M.gguf 46.5 GB 1dbad574 download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q5_K_S.gguf 45.3 GB 2c7db86b download
Q4_K 2 files 77.2 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q4_K_M.gguf 39.6 GB 94c9c4ce download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q4_K_S.gguf 37.6 GB 00e1102b download
IQ4 1 file 35.6 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.IQ4_XS.gguf 35.6 GB b7c82850 download
Q3_K 3 files 95.3 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q3_K_L.gguf 34.6 GB 2d240522 download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q3_K_M.gguf 31.9 GB 16b8300c download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q3_K_S.gguf 28.8 GB 9a4845df download
Q2_K 1 file 24.6 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q2_K.gguf 24.6 GB 67ae5314 download
Auxiliary files 6 files 124 GB
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q8_0.gguf.part1of2 35.0 GB 6629a95f download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q8_0.gguf.part2of2 34.8 GB 8f381682 download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q6_K.gguf.part1of2 27.0 GB c1810b39 download
Llama_3.x_70b-Nemotron-L3.3_abliterated_fusion_v2.Q6_K.gguf.part2of2 26.9 GB cbf2f3d4 download
README.md 4.48 KB 67dc7382 download
.gitattributes 2.75 KB 4686e2cb download

README current version from Hugging Face


base_model: Nexesenex/Llama_3.x_70b_Nemotron-L3.3_abliterated_fusion_v2
language:

  • en
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • mergekit
  • merge

About

static quants of https://huggingface.co/Nexesenex/Llama_3.x_70b_Nemotron-L3.3_abliterated_fusion_v2

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 26.5
GGUF Q3_K_S 31.0
GGUF Q3_K_M 34.4 lower quality
GGUF Q3_K_L 37.2
GGUF IQ4_XS 38.4
GGUF Q4_K_S 40.4 fast, recommended
GGUF Q4_K_M 42.6 fast, recommended
GGUF Q5_K_S 48.8
GGUF Q5_K_M 50.0
PART 1 PART 2 Q6_K 58.0 very good quality
PART 1 PART 2 Q8_0 75.1 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

README history 6 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-07-31auto-patch README.mdfffd17a4.5 KB
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  2. 2025-07-11auto-patch README.mdc10707d4.7 KB
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  3. 2025-07-10auto-patch README.mdc5c7a414.7 KB
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  4. 2025-04-20auto-patch README.md09775534.5 KB
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  5. 2025-04-20auto-patch README.mda223db03.9 KB
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  6. 2025-04-20uploaded from nico1c6b53a8249 B
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