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mradermacher/Prosopon-31B-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…

transformersggufmergemergekitlm-head-transplantreasoningnon-reasoningcreative writingswipe varietyroleplayconversationalcharacter-rplow-refusalnsfw31Bgemma-4enbase_model:Nimbz/Prosopon-31Bbase_model:quantized:Nimbz/Prosopon-31Blicense:apache-2.0endpoints_compatibleregion:usimatrix

Runs locally from ~13.1 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
Prosopon-31B.i1-IQ1_M.ggufGGUFIQ1_M7.63 GBDownload
Prosopon-31B.i1-IQ1_S.ggufGGUFIQ1_S7.10 GBDownload
Prosopon-31B.i1-IQ2_M.ggufGGUFIQ2_M10.73 GBDownload
Prosopon-31B.i1-IQ2_S.ggufGGUFIQ2_S10.02 GBDownload
Prosopon-31B.i1-IQ2_XS.ggufGGUFIQ2_XS9.31 GBDownload
Prosopon-31B.i1-IQ2_XXS.ggufGGUFIQ2_XXS8.51 GBDownload
Prosopon-31B.i1-IQ3_M.ggufGGUFIQ3_M14.00 GBDownload
Prosopon-31B.i1-IQ3_S.ggufGGUFIQ3_S13.38 GBDownload
Prosopon-31B.i1-IQ3_XS.ggufGGUFIQ3_XS12.74 GBDownload
Prosopon-31B.i1-IQ3_XXS.ggufGGUFIQ3_XXS11.81 GBDownload
Prosopon-31B.i1-IQ4_XS.ggufGGUFIQ4_XS16.28 GBDownload
Prosopon-31B.i1-Q2_K.ggufGGUFQ2_K11.53 GBDownload
Prosopon-31B.i1-Q2_K_S.ggufGGUFQ2_K_S10.65 GBDownload
Prosopon-31B.i1-Q3_K_L.ggufGGUFQ3_K_L16.05 GBDownload
Prosopon-31B.i1-Q3_K_M.ggufGGUFQ3_K_M14.80 GBDownload
Prosopon-31B.i1-Q3_K_S.ggufGGUFQ3_K_S13.38 GBDownload
Prosopon-31B.i1-Q4_0.ggufGGUFQ4_017.22 GBDownload
Prosopon-31B.i1-Q4_1.ggufGGUFQ4_118.96 GBDownload
Prosopon-31B.i1-Q4_K_M.ggufGGUFQ4_K_M18.14 GBDownload
Prosopon-31B.i1-Q4_K_S.ggufGGUFQ4_K_S17.28 GBDownload
Prosopon-31B.i1-Q5_K_M.ggufGGUFQ5_K_M21.25 GBDownload
Prosopon-31B.i1-Q5_K_S.ggufGGUFQ5_K_S20.75 GBDownload
Prosopon-31B.i1-Q6_K.ggufGGUFQ6_K24.55 GBDownload
Prosopon-31B.imatrix.ggufGGUFGGUF13.1 MBDownload

Model Details

Model IDmradermacher/Prosopon-31B-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelNimbz/Prosopon-31B
Last modified2026-07-09T17:19:23.000Z

Model README

---

base_model: Nimbz/Prosopon-31B

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • merge
  • mergekit
  • lm-head-transplant
  • reasoning
  • non-reasoning
  • creative writing
  • swipe variety
  • roleplay
  • conversational
  • character-rp
  • low-refusal
  • nsfw
  • 31B
  • gemma-4

---

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: 1 -->

weighted/imatrix quants of https://huggingface.co/Nimbz/Prosopon-31B

<!-- 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/Prosopon-31B-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 | 7.7 | for the desperate |

| GGUF | i1-IQ1_M | 8.3 | mostly desperate |

| GGUF | i1-IQ2_XXS | 9.2 | |

| GGUF | i1-IQ2_XS | 10.1 | |

| GGUF | i1-IQ2_S | 10.9 | |

| GGUF | i1-Q2_K_S | 11.5 | very low quality |

| GGUF | i1-IQ2_M | 11.6 | |

| GGUF | i1-Q2_K | 12.5 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 12.8 | lower quality |

| GGUF | i1-IQ3_XS | 13.8 | |

| GGUF | i1-IQ3_S | 14.5 | beats Q3_K* |

| GGUF | i1-Q3_K_S | 14.5 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 15.1 | |

| GGUF | i1-Q3_K_M | 16.0 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 17.3 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 17.6 | |

| GGUF | i1-Q4_0 | 18.6 | fast, low quality |

| GGUF | i1-Q4_K_S | 18.7 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 19.6 | fast, recommended |

| GGUF | i1-Q4_1 | 20.5 | |

| GGUF | i1-Q5_K_S | 22.4 | |

| GGUF | i1-Q5_K_M | 22.9 | |

| GGUF | i1-Q6_K | 26.5 | 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.

<!-- end -->

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