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

mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-v2-i1-GGUF

mradermacher Llama 17B GGUF second-order 10.5M ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FLlama-4-Scout-17B-16E-Instruct-abliterated-v2-i1-GGUF"
Response includes
  • classification m8
  • files 36
  • hub_downloads_all_time 21,187
  • author_summary 3324 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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='jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated-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
21K
1K last 30d - cooling
Likes
7
Model age
16mo ago
created 2025-06-08
Downloads over time
Now21.5K→from892↑2,314%
07.9K15.7K23.6K892 on Jun 19, 202521.5K on Oct 11Jun '25Sep '25Dec '25MarJunSep
Jun 19, 2025 → Oct 11 · 108 snapshots · spans 479 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 · 2K downloads combined

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

Metadata

Languages
ar de en es fr hi id it pt th tl vi
Quantizations
IQ1 IQ2 IQ3 Q2_K Q3_K
Tags
transformers gguf facebook meta pytorch llama llama4 ar de en es fr

Related

Total size
446 GB
Files
36
Quantizations
6
Registered
2026-08-22 13:56
Last updated on HF
2025-07-11 01:05

Files by quantization

IQ3 4 files 168 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ3_M.gguf 44.2 GB 47e2e728 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ3_S.gguf 43.6 GB b54ba934 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ3_XS.gguf 41.3 GB 3266fc93 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ3_XXS.gguf 38.8 GB 3526c359 download
Q3_K 1 file 43.5 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q3_K_S.gguf 43.5 GB 0adf3cbd download
Q2_K 2 files 71.3 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q2_K.gguf 36.8 GB a104b495 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q2_K_S.gguf 34.4 GB 9e957f55 download
IQ2 4 files 119 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ2_M.gguf 33.0 GB 4c972956 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ2_S.gguf 30.1 GB 58461806 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ2_XS.gguf 29.6 GB 1470e9b0 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ2_XXS.gguf 26.6 GB 7da4b1b9 download
IQ1 2 files 43.5 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ1_M.gguf 22.9 GB c4b1be69 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ1_S.gguf 20.7 GB bf41b88e download
Auxiliary files 23 files 615 GB
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q6_K.gguf.part1of2 42.0 GB d451f9e6 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q6_K.gguf.part2of2 40.4 GB a7465a33 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q5_K_M.gguf.part1of2 36.0 GB 49cf413e download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q5_K_M.gguf.part2of2 35.3 GB e210aa17 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q5_K_S.gguf.part1of2 35.0 GB 63d09b7d download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q5_K_S.gguf.part2of2 34.2 GB dad4d3ca download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_1.gguf.part1of2 32.0 GB e632fc8a download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_K_M.gguf.part1of2 31.0 GB dcff6948 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_1.gguf.part2of2 30.9 GB 9d404186 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_K_M.gguf.part2of2 29.9 GB fc9a4a71 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_0.gguf.part1of2 29.0 GB 3cd8b650 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_K_S.gguf.part1of2 29.0 GB e6034983 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_K_S.gguf.part2of2 28.2 GB b3070935 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q4_0.gguf.part2of2 28.0 GB 139d070e download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ4_XS.gguf.part1of2 27.0 GB 352c2443 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q3_K_L.gguf.part1of2 27.0 GB a9e3cf0c download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-IQ4_XS.gguf.part2of2 26.7 GB afbcbde5 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q3_K_L.gguf.part2of2 25.1 GB 3f3185ef download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q3_K_M.gguf.part1of2 25.0 GB 541d30a9 download
Llama-4-Scout-17B-16E-Instruct-abliterated-v2.i1-Q3_K_M.gguf.part2of2 23.2 GB 0dabac4d download
imatrix.dat 62.1 MB dc5134da download
README.md 8.86 KB c3223e8b download
.gitattributes 4.81 KB 17dc408d download

README current version from Hugging Face


base_model: jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated-v2
language:

  • ar
  • de
  • en
  • es
  • fr
  • hi
  • id
  • it
  • pt
  • th
  • tl
  • vi
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • facebook
  • meta
  • pytorch
  • llama
  • llama4

About

weighted/imatrix quants of https://huggingface.co/jiangchengchengNLP/Llama-4-Scout-17B-16E-Instruct-abliterated-v2

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

static quants are available at https://huggingface.co/mradermacher/Llama-4-Scout-17B-16E-Instruct-abliterated-v2-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

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 i1-IQ1_S 22.3 for the desperate
GGUF i1-IQ1_M 24.7 mostly desperate
GGUF i1-IQ2_XXS 28.7
GGUF i1-IQ2_XS 31.9
GGUF i1-IQ2_S 32.4
GGUF i1-IQ2_M 35.6
GGUF i1-Q2_K_S 37.1 very low quality
GGUF i1-Q2_K 39.7 IQ3_XXS probably better
GGUF i1-IQ3_XXS 41.8 lower quality
GGUF i1-IQ3_XS 44.4
GGUF i1-Q3_K_S 46.8 IQ3_XS probably better
GGUF i1-IQ3_S 46.9 beats Q3_K*
GGUF i1-IQ3_M 47.6
PART 1 PART 2 i1-Q3_K_M 51.9 IQ3_S probably better
PART 1 PART 2 i1-Q3_K_L 56.1 IQ3_M probably better
PART 1 PART 2 i1-IQ4_XS 57.7
PART 1 PART 2 i1-Q4_0 61.3 fast, low quality
PART 1 PART 2 i1-Q4_K_S 61.6 optimal size/speed/quality
PART 1 PART 2 i1-Q4_K_M 65.5 fast, recommended
PART 1 PART 2 i1-Q4_1 67.7
PART 1 PART 2 i1-Q5_K_S 74.4
PART 1 PART 2 i1-Q5_K_M 76.6
PART 1 PART 2 i1-Q6_K 88.5 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 5 versions

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

  1. 2025-07-11auto-patch README.md409d8f28.9 KB
    Loading...
  2. 2025-07-10auto-patch README.mdf9d32ba8.8 KB
    Loading...
  3. 2025-07-10auto-patch README.md6670a5f8.9 KB
    Loading...
  4. 2025-06-09auto-patch README.md872656b8.5 KB
    Loading...
  5. 2025-06-08uploaded from nico12900c67272 B
    Loading...

Discussions 2 threads

  1. 2026-07-26not loading in lmstudioopen2 💬#2
    Loading...
  2. 2026-05-27defective gguf filesopen4 💬#1
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration