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Riyan200324200324/Qwen3-Next-80B-A3B-Instruct-Decensored-i1-GGUF

Riyan200324200324 80B GGUF MoE
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  • classification unknown
  • files 26
  • author_summary 14 models
  • readme_text full
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Abliteration classifier · v1.0.0
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  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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created 2026-10-06

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Metadata

Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf generated_from_trainer dpo trl en base_model:Shifusen/Qwen3-Next-80B-A3B-Instruct-Decensored base_model:quantized:Shifusen/Qwen3-Next-80B-A3B-Instruct-Decensored endpoints_compatible region:us imatrix conversational

Related

Total size
783 GB
Files
26
Quantizations
11
Registered
2026-10-06 07:58
Last updated on HF
2026-10-06 07:21

Files by quantization

Q6_K 1 file 61.0 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q6_K.gguf 61.0 GB 91ba3bd5 download
Q5_K 2 files 104 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q5_K_M.gguf 52.8 GB 25f49c16 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q5_K_S.gguf 51.2 GB 4cfdaafe download
Q4 2 files 88.8 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q4_1.gguf 46.6 GB 26feff9e download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q4_0.gguf 42.2 GB 3e2cdf4a download
Q4_K 2 files 87.4 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q4_K_M.gguf 45.1 GB 9c6679f3 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q4_K_S.gguf 42.4 GB ac369ebb download
IQ4 1 file 39.7 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ4_XS.gguf 39.7 GB 81e85c30 download
Q3_K 3 files 106 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q3_K_L.gguf 38.4 GB bb243059 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q3_K_M.gguf 35.6 GB 1d2c02d3 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q3_K_S.gguf 32.2 GB e2248fc2 download
IQ3 4 files 124 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ3_M.gguf 32.6 GB 1c9374fc download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ3_S.gguf 32.2 GB d322fb8c download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ3_XS.gguf 30.5 GB 8c2f1a50 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ3_XXS.gguf 28.7 GB 64b35260 download
Q2_K 2 files 52.5 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q2_K.gguf 27.1 GB 4f93a487 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-Q2_K_S.gguf 25.4 GB b5d458cf download
IQ2 4 files 87.7 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ2_M.gguf 24.3 GB e660fd95 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ2_S.gguf 22.0 GB 380aae5a download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ2_XS.gguf 21.8 GB 5aff22b7 download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ2_XXS.gguf 19.6 GB c758e3c0 download
IQ1 2 files 31.8 GB
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ1_M.gguf 16.8 GB 97ddb54c download
Qwen3-Next-80B-A3B-Instruct-Decensored.i1-IQ1_S.gguf 15.1 GB 12e969bc download
Auxiliary files 3 files 436 MB
Qwen3-Next-80B-A3B-Instruct-Decensored.imatrix.gguf 436 MB 1325c38b download
README.md 6.85 KB 30643ecc download
.gitattributes 3.58 KB a293a5ea download

README current version from Hugging Face


base_model: Shifusen/Qwen3-Next-80B-A3B-Instruct-Decensored
language:

  • en
    library_name: transformers
    model_name: outputs/dpo-out
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • generated_from_trainer
  • dpo
  • trl

About

weighted/imatrix quants of https://huggingface.co/Shifusen/Qwen3-Next-80B-A3B-Instruct-Decensored

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

static quants are available at https://huggingface.co/mradermacher/Qwen3-Next-80B-A3B-Instruct-Decensored-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 0.6 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 16.3 for the desperate
GGUF i1-IQ1_M 18.1 mostly desperate
GGUF i1-IQ2_XXS 21.1
GGUF i1-IQ2_XS 23.5
GGUF i1-IQ2_S 23.7
GGUF i1-IQ2_M 26.2
GGUF i1-Q2_K_S 27.4 very low quality
GGUF i1-Q2_K 29.2 IQ3_XXS probably better
GGUF i1-IQ3_XXS 30.9 lower quality
GGUF i1-IQ3_XS 32.8
GGUF i1-Q3_K_S 34.6 IQ3_XS probably better
GGUF i1-IQ3_S 34.6 beats Q3_K*
GGUF i1-IQ3_M 35.1
GGUF i1-Q3_K_M 38.3 IQ3_S probably better
GGUF i1-Q3_K_L 41.3 IQ3_M probably better
GGUF i1-IQ4_XS 42.7
GGUF i1-Q4_0 45.4 fast, low quality
GGUF i1-Q4_K_S 45.6 optimal size/speed/quality
GGUF i1-Q4_K_M 48.5 fast, recommended
GGUF i1-Q4_1 50.1
GGUF i1-Q5_K_S 55.1
GGUF i1-Q5_K_M 56.8
GGUF i1-Q6_K 65.6 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.

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