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mradermacher/Gemma-4-26B-A4B-StyleTune-V2-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…

transformersggufgemma4conversationalinstructfinetuneroleplaycreative-writingstyle-tuneenbase_model:Gryphe/Gemma-4-26B-A4B-StyleTune-V2base_model:quantized:Gryphe/Gemma-4-26B-A4B-StyleTune-V2license:apache-2.0endpoints_compatibleregion:usimatrix

Runs locally from ~54.3 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
13,027
Likes
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Pipeline

Repository Files & Downloads

24 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ1_M.ggufGGUFIQ1_M8.30 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ1_S.ggufGGUFIQ1_S7.95 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ2_M.ggufGGUFIQ2_M9.96 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ2_S.ggufGGUFIQ2_S9.49 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ2_XS.ggufGGUFIQ2_XS9.37 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ2_XXS.ggufGGUFIQ2_XXS8.89 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ3_M.ggufGGUFIQ3_M11.84 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ3_S.ggufGGUFIQ3_S11.68 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ3_XS.ggufGGUFIQ3_XS11.13 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ3_XXS.ggufGGUFIQ3_XXS10.84 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-IQ4_XS.ggufGGUFIQ4_XS13.33 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q2_K.ggufGGUFQ2_K10.08 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q2_K_S.ggufGGUFQ2_K_S10.12 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q3_K_L.ggufGGUFQ3_K_L13.17 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q3_K_M.ggufGGUFQ3_K_M12.67 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q3_K_S.ggufGGUFQ3_K_S11.68 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q4_0.ggufGGUFQ4_013.88 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q4_1.ggufGGUFQ4_115.30 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q4_K_M.ggufGGUFQ4_K_M16.03 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q4_K_S.ggufGGUFQ4_K_S14.79 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q5_K_M.ggufGGUFQ5_K_M18.29 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q5_K_S.ggufGGUFQ5_K_S17.22 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.i1-Q6_K.ggufGGUFQ6_K21.65 GBDownload
Gemma-4-26B-A4B-StyleTune-V2.imatrix.ggufGGUFGGUF54.3 MBDownload

Model Details

Model IDmradermacher/Gemma-4-26B-A4B-StyleTune-V2-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelGryphe/Gemma-4-26B-A4B-StyleTune-V2
Last modified2026-07-03T12:19:01.000Z

Model README

---

base_model: Gryphe/Gemma-4-26B-A4B-StyleTune-V2

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • gemma4
  • conversational
  • instruct
  • finetune
  • roleplay
  • creative-writing
  • style-tune

---

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/Gryphe/Gemma-4-26B-A4B-StyleTune-V2

<!-- 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/Gemma-4-26B-A4B-StyleTune-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](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 | 0.2 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 8.6 | for the desperate |

| GGUF | i1-IQ1_M | 9.0 | mostly desperate |

| GGUF | i1-IQ2_XXS | 9.6 | |

| GGUF | i1-IQ2_XS | 10.2 | |

| GGUF | i1-IQ2_S | 10.3 | |

| GGUF | i1-IQ2_M | 10.8 | |

| GGUF | i1-Q2_K | 10.9 | IQ3_XXS probably better |

| GGUF | i1-Q2_K_S | 11.0 | very low quality |

| GGUF | i1-IQ3_XXS | 11.7 | lower quality |

| GGUF | i1-IQ3_XS | 12.1 | |

| GGUF | i1-IQ3_S | 12.6 | beats Q3_K* |

| GGUF | i1-Q3_K_S | 12.6 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 12.8 | |

| GGUF | i1-Q3_K_M | 13.7 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 14.2 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 14.4 | |

| GGUF | i1-Q4_0 | 15.0 | fast, low quality |

| GGUF | i1-Q4_K_S | 16.0 | optimal size/speed/quality |

| GGUF | i1-Q4_1 | 16.5 | |

| GGUF | i1-Q4_K_M | 17.3 | fast, recommended |

| GGUF | i1-Q5_K_S | 18.6 | |

| GGUF | i1-Q5_K_M | 19.7 | |

| GGUF | i1-Q6_K | 23.3 | 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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