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Riyan200324200324/GLM-4.7-Flash-Uncensored-MAX-GGUF

Riyan200324200324 Glm GGUF second-order
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created 2026-10-06

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Metadata

License
mit
Languages
en zh
Quantizations
IQ2 IQ3 IQ4 Q4 Q4_K Q5 Q5_K Q6_K Q8_0
Tags
gguf GLM 4.7 Flash thinking reasoning NEO Imatrix MAX Quants 16 bit precision output tensor heretic uncensored abliterated deep reasoning fine tune

Related

Total size
219 GB
Files
14
Quantizations
10
Registered
2026-10-06 06:58
Last updated on HF
2026-10-06 06:03

Files by quantization

Q8_0 1 file 29.9 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q8_0.gguf 29.9 GB 6e13bc93 download
Q6_K 1 file 23.3 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q6_K.gguf 23.3 GB 544d5b58 download
Q5 1 file 21.3 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q5_1.gguf 21.3 GB 9408b81c download
Q5_K 2 files 39.7 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q5_K_M.gguf 20.2 GB 444467bf download
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q5_K_S.gguf 19.6 GB dba1f084 download
Q4 1 file 17.9 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q4_1.gguf 17.9 GB f1f902ab download
Q4_K 2 files 33.5 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q4_K_M.gguf 17.2 GB 6eb0adad download
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-Q4_K_S.gguf 16.2 GB 9ff44d89 download
IQ4 2 files 31.4 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-IQ4_NL.gguf 16.1 GB 8dad4615 download
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-IQ4_XS.gguf 15.3 GB c0e55948 download
IQ3 1 file 12.7 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-IQ3_M.gguf 12.7 GB 4dc6b9ca download
IQ2 1 file 9.61 GB
GLM-4.7-Flash-Uncen-Hrt-NEO-CODE-MAX-imat-D_AU-IQ2_M.gguf 9.61 GB 7ea32884 download
Auxiliary files 2 files 8.45 KB
README.md 5.86 KB 42cae13e download
.gitattributes 2.59 KB 436ac408 download

README current version from Hugging Face


language:

  • en
  • zh
    license: mit
    tags:
  • GLM 4.7 Flash
  • thinking
  • reasoning
  • NEO Imatrix
  • MAX Quants
  • 16 bit precision output tensor
  • heretic
  • uncensored
  • abliterated
  • thinking
  • reasoning
  • deep reasoning
  • fine tune
  • creative
  • creative writing
  • fiction writing
  • plot generation
  • sub-plot generation
  • fiction writing
  • story generation
  • scene continue
  • storytelling
  • fiction story
  • science fiction
  • romance
  • all genres
  • story
  • writing
  • vivid prosing
  • vivid writing
  • fiction
  • roleplaying
  • bfloat16
  • swearing
  • rp
  • horror
    pipeline_tag: text-generation
    base_model:
  • Olafangensan/GLM-4.7-Flash-heretic

GLM-4.7-Flash-Uncensored-Heretic-NEO-CODE-Imatrix-MAX-GGUF

Specialized and Enhanced UNCENSORED/HERETIC GGUF quants for the new GLM-4.7-Flash, 30B-A3B MOE, mixture of experts model.

[ https://huggingface.co/zai-org/GLM-4.7-Flash ]

This model can be run on the GPU(s) and/or CPU due to 4 experts activated (appox 2B parameters active).

Uncensored / Heretic'ed

De-censoring by Heretic (special thanks to "Olafangensan") seems to have reduced the size of thinking blocks in some cases
and/or "focused" the model more.

Default Settings (Most Tasks)

temperature: 1.0
top-p: 0.95
max new tokens: 131072

REP PEN: 1.1 OR 1.0 (off) (if you get repeat issues)

You might also try GLM 4.6 settings (unsloth):

temperature = 0.8

top_p = 0.6 (recommended)

top_k = 2 (recommended)

max_generate_tokens = 16,384

That being said, I suggest min context of 8k-16K as final outputs (post thinking) can be long and detailed and in a number
of cases has been observed "polishing" the final output one or more times IN the output section.

(Model can handle 200k context, non-roped.)

NON-UNCENSORED QUANTS:

https://huggingface.co/DavidAU/GLM-4.7-Flash-Uncensored-Heretic-NEO-CODE-Imatrix-MAX-GGUF

Quants General:

Quants and Imatrixes computed using latest LLAMACPP (commit: 7789, Jan 21 2026) which contains specific fixes for this model.

Quants prior to this commit (as well as Imatrix generation) performed poorly (re-quanization and re-imatrix generation are required).

Also note there are some issues with Flash Attn and low token generation speed (as Flash is offloaded to CPU in some cases). Disable
Flash Attn until this issue is resolved / makes its way thru the "llamacpp / ai pipeline".

Specialized Quants

Specialized quants (IQ4_NL, Q5_1, Q4_1, Q8_0) are precision balanced to address a specific tensor issues in all layers
that requires a specific quant type.

Other "normal" quants will also perform very well.

Quant Enhancements:

Imatrix is NEO and Code datasets by DavidAU - Dual Imatrix (2 imatrixes separately generated) to improve model performance.

All quants (specialized and "normal") are also enhanced with 16 bit (full) precision "output tensor" to further improve model performance.

Output tensor affects 10-20% of the fine output of the model - both thinking and output (final) generation.

Special thanks to :

  • Team ZAI-ORG for making an outstanding model.
  • Team P-E-W for fanstastic work on Heretic system.
  • Team Olafangensan for Heretic'ing the model.

Using an "uncensored" (refusals removed) model VS trained "uncensored" model

Usually when you a tell a model to generate horror, swear or x-rated content this is all you have to do to get said content type.

In the case of this model, it will not refuse your request, however it needs to be "pushed" a bit / directed a bit more in SOME CASES.

Although this model will generated x-rated content too, likewise you need to tell it to use "slang" (and include the terms you want)
to get it generate the content correctly as the "expected" content level too.

Without these added directive(s), the content can be "bland" by comparison to an "uncensored model" or model trained on uncensored content.

Roughly, the model tries to generate the content but the "default" setting(s) are so "tame" it needs a push to generate at expected graphic,
cursing or explicit levels.

Even with minimal direction (ie, use these words to swear: x,y,z), this will be enough to push the model to generate the requested content in the ahh... expected format.


Settings: CHAT / ROLEPLAY and/or SMOOTHER operation of this model:

In "KoboldCpp" or "oobabooga/text-generation-webui" or "Silly Tavern" ;

Set the "Smoothing_factor" to 1.5

: in KoboldCpp -> Settings->Samplers->Advanced-> "Smooth_F"

: in text-generation-webui -> parameters -> lower right.

: In Silly Tavern this is called: "Smoothing"

NOTE: For "text-generation-webui"

-> if using GGUFs you need to use "llama_HF" (which involves downloading some config files from the SOURCE version of this model)

Source versions (and config files) of my models are here:

https://huggingface.co/collections/DavidAU/d-au-source-files-for-gguf-exl2-awq-gptq-hqq-etc-etc-66b55cb8ba25f914cbf210be

OTHER OPTIONS:

  • Increase rep pen to 1.1 to 1.15 (you don't need to do this if you use "smoothing_factor")

  • If the interface/program you are using to run AI MODELS supports "Quadratic Sampling" ("smoothing") just make the adjustment as noted.

Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers

This a "Class 1" model:

For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) please see:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

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