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mradermacher/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated-i1-GGUF

mradermacher Nemotron 8B GGUF second-order 1.1M ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2Fnvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated-i1-GGUF"
Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 7,377
  • 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='Nitral-Archive/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated' (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.

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Downloads · lifetime
7K
942 last 30d - stable
Likes
0
Model age
7mo ago
created 2026-02-27
Downloads over time
Now7.7K→from2.9K↑166%
2.6K4.5K6.3K8.2K2.9K on Feb 257.7K on Oct 11FebAprJunAugOct
Feb 25 → Oct 11 · 72 snapshots · spans 228 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.

Variants by this author 2 formats · 1K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf en base_model:Nitral-Archive/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated base_model:quantized:Nitral-Archive/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated endpoints_compatible region:us imatrix conversational

Related

Total size
87.5 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-02-27 12:55

Files by quantization

Q6_K 1 file 6.15 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q6_K.gguf 6.15 GB c9da1091 download
Q5_K 2 files 10.6 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q5_K_M.gguf 5.34 GB 1a9d6302 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q5_K_S.gguf 5.22 GB 9d09b38b download
Q4 2 files 9.14 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q4_1.gguf 4.78 GB 6ba30753 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q4_0.gguf 4.36 GB 645000b9 download
Q4_K 2 files 8.96 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q4_K_M.gguf 4.59 GB dc783904 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q4_K_S.gguf 4.37 GB e6eafc92 download
IQ4 2 files 8.51 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ4_NL.gguf 4.36 GB 2eb9cf9b download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ4_XS.gguf 4.15 GB 6e75c232 download
Q3_K 3 files 11.2 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q3_K_L.gguf 4.03 GB 89fcb509 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q3_K_M.gguf 3.75 GB c695cc1d download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q3_K_S.gguf 3.42 GB a35c7b81 download
IQ3 4 files 13.3 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ3_M.gguf 3.53 GB 9c88680a download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ3_S.gguf 3.43 GB 91bf0266 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ3_XS.gguf 3.28 GB e5528d76 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ3_XXS.gguf 3.05 GB f4315105 download
Q2_K 2 files 5.75 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q2_K.gguf 2.96 GB 4b622f20 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-Q2_K_S.gguf 2.79 GB 5209fe22 download
IQ2 4 files 9.99 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ2_M.gguf 2.75 GB ba48a332 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ2_S.gguf 2.57 GB 90ff6856 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ2_XS.gguf 2.43 GB 1a5181ef download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ2_XXS.gguf 2.24 GB 53a0e31f download
IQ1 2 files 3.90 GB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ1_M.gguf 2.02 GB 5323d616 download
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.i1-IQ1_S.gguf 1.88 GB 608811f0 download
Auxiliary files 3 files 4.80 MB
nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated.imatrix.gguf 4.78 MB c1dab5e6 download
README.md 8.23 KB 7753777a download
.gitattributes 4.25 KB 7fb9655b download

README current version from Hugging Face


base_model: Nitral-Archive/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated
language:

  • en
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/Nitral-Archive/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated

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

static quants are available at https://huggingface.co/mradermacher/nvidia_Llama-3.1-Nemotron-8B-UltraLong-1M-Instruct-abliterated-GGUF

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 imatrix 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 2.1 for the desperate
GGUF i1-IQ1_M 2.3 mostly desperate
GGUF i1-IQ2_XXS 2.5
GGUF i1-IQ2_XS 2.7
GGUF i1-IQ2_S 2.9
GGUF i1-IQ2_M 3.1
GGUF i1-Q2_K_S 3.1 very low quality
GGUF i1-Q2_K 3.3 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.4 lower quality
GGUF i1-IQ3_XS 3.6
GGUF i1-Q3_K_S 3.8 IQ3_XS probably better
GGUF i1-IQ3_S 3.8 beats Q3_K*
GGUF i1-IQ3_M 3.9
GGUF i1-Q3_K_M 4.1 IQ3_S probably better
GGUF i1-Q3_K_L 4.4 IQ3_M probably better
GGUF i1-IQ4_XS 4.6
GGUF i1-Q4_0 4.8 fast, low quality
GGUF i1-IQ4_NL 4.8 prefer IQ4_XS
GGUF i1-Q4_K_S 4.8 optimal size/speed/quality
GGUF i1-Q4_K_M 5.0 fast, recommended
GGUF i1-Q4_1 5.2
GGUF i1-Q5_K_S 5.7
GGUF i1-Q5_K_M 5.8
GGUF i1-Q6_K 6.7 practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

README history 3 versions

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

  1. 2026-02-27auto-patch README.md86a9bdf8.2 KB
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  2. 2026-02-27auto-patch README.md4ebde9e6.2 KB
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  3. 2026-02-27uploaded from marco952ee52523 B
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