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mradermacher/Q3.6-27B-GLM-5.1-DA-i1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss < quants: Q2 K IQ3 M Q4 K S IQ3 XXS Q3 K M small IQ4…

transformersgguftext-generation-inferenceglm-5.1mathreasoningpytorchuncensoredabliteratedunfilteredunredactedrefusal-ablatedalignment-modifiedbf16endataset:prithivMLmods/harm_benchdataset:Jackrong/GLM-5.1-Reasoning-1M-Cleanedbase_model:prithivMLmods/Q3.6-27B-GLM-5.1-DAbase_model:quantized:prithivMLmods/Q3.6-27B-GLM-5.1-DAlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~13.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

24 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Q3.6-27B-GLM-5.1-DA.i1-IQ1_M.ggufGGUFQ37.11 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ1_S.ggufGGUFQ36.66 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ2_M.ggufGGUFQ39.32 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ2_S.ggufGGUFQ38.72 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ2_XS.ggufGGUFQ38.47 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ2_XXS.ggufGGUFQ37.85 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ3_M.ggufGGUFQ311.72 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ3_S.ggufGGUFQ311.57 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ3_XS.ggufGGUFQ311.15 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ3_XXS.ggufGGUFQ310.42 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-IQ4_XS.ggufGGUFQ314.05 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q2_K.ggufGGUFQ39.98 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q2_K_S.ggufGGUFQ39.54 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q3_K_L.ggufGGUFQ313.36 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q3_K_M.ggufGGUFQ312.39 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q3_K_S.ggufGGUFQ311.24 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q4_0.ggufGGUFQ314.46 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q4_1.ggufGGUFQ315.91 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q4_K_M.ggufGGUFQ315.41 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q4_K_S.ggufGGUFQ314.52 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q5_K_M.ggufGGUFQ317.91 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q5_K_S.ggufGGUFQ317.40 GBDownload
Q3.6-27B-GLM-5.1-DA.i1-Q6_K.ggufGGUFQ320.57 GBDownload
Q3.6-27B-GLM-5.1-DA.imatrix.ggufGGUFQ313.0 MBDownload

Model Details

Model IDmradermacher/Q3.6-27B-GLM-5.1-DA-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelprithivMLmods/Q3.6-27B-GLM-5.1-DA
Last modified2026-07-07T16:42:44.000Z

Model README

---

base_model: prithivMLmods/Q3.6-27B-GLM-5.1-DA

datasets:

  • prithivMLmods/harm_bench
  • Jackrong/GLM-5.1-Reasoning-1M-Cleaned

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • text-generation-inference
  • glm-5.1
  • math
  • reasoning
  • pytorch
  • uncensored
  • abliterated
  • unfiltered
  • unredacted
  • refusal-ablated
  • alignment-modified
  • bf16

---

About

<!-- ### quantize_version: 2 -->

<!-- ### output_tensor_quantised: 1 -->

<!-- ### convert_type: hf -->

<!-- ### vocab_type: -->

<!-- ### tags: nicoboss -->

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/prithivMLmods/Q3.6-27B-GLM-5.1-DA

<!-- provided-files -->

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

static quants are available at https://huggingface.co/mradermacher/Q3.6-27B-GLM-5.1-DA-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](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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 | 7.2 | for the desperate |

| GGUF | i1-IQ1_M | 7.7 | mostly desperate |

| GGUF | i1-IQ2_XXS | 8.5 | |

| GGUF | i1-IQ2_XS | 9.2 | |

| GGUF | i1-IQ2_S | 9.5 | |

| GGUF | i1-IQ2_M | 10.1 | |

| GGUF | i1-Q2_K_S | 10.3 | very low quality |

| GGUF | i1-Q2_K | 10.8 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 11.3 | lower quality |

| GGUF | i1-IQ3_XS | 12.1 | |

| GGUF | i1-Q3_K_S | 12.2 | IQ3_XS probably better |

| GGUF | i1-IQ3_S | 12.5 | beats Q3_K* |

| GGUF | i1-IQ3_M | 12.7 | |

| GGUF | i1-Q3_K_M | 13.4 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 14.4 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 15.2 | |

| GGUF | i1-Q4_0 | 15.6 | fast, low quality |

| GGUF | i1-Q4_K_S | 15.7 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 16.6 | fast, recommended |

| GGUF | i1-Q4_1 | 17.2 | |

| GGUF | i1-Q5_K_S | 18.8 | |

| GGUF | i1-Q5_K_M | 19.3 | |

| GGUF | i1-Q6_K | 22.2 | 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.

<!-- end -->

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