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mradermacher/Newton-bot-3-VLM-mini-4B-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…

transformersggufNewtonBotFamilyTreeimage-text-to-textgeminiunslothruenfrukbepldataset:TeichAI/gemini-3-flash-previewbase_model:Kolyadual/Newton-bot-3-VLM-mini-4Bbase_model:quantized:Kolyadual/Newton-bot-3-VLM-mini-4Blicense:gpl-3.0endpoints_compatibleregion:usconversational

Runs locally from ~349.9 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
image-text-to-text

Repository Files & Downloads

14 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Newton-bot-3-VLM-mini-4B.IQ4_XS.ggufGGUFGGUF2.42 GBDownload
Newton-bot-3-VLM-mini-4B.Q2_K.ggufGGUFGGUF1.82 GBDownload
Newton-bot-3-VLM-mini-4B.Q3_K_L.ggufGGUFGGUF2.31 GBDownload
Newton-bot-3-VLM-mini-4B.Q3_K_M.ggufGGUFGGUF2.16 GBDownload
Newton-bot-3-VLM-mini-4B.Q3_K_S.ggufGGUFGGUF1.98 GBDownload
Newton-bot-3-VLM-mini-4B.Q4_K_M.ggufGGUFGGUF2.59 GBDownload
Newton-bot-3-VLM-mini-4B.Q4_K_S.ggufGGUFGGUF2.45 GBDownload
Newton-bot-3-VLM-mini-4B.Q5_K_M.ggufGGUFGGUF2.94 GBDownload
Newton-bot-3-VLM-mini-4B.Q5_K_S.ggufGGUFGGUF2.86 GBDownload
Newton-bot-3-VLM-mini-4B.Q6_K.ggufGGUFGGUF3.32 GBDownload
Newton-bot-3-VLM-mini-4B.Q8_0.ggufGGUFGGUF4.29 GBDownload
Newton-bot-3-VLM-mini-4B.f16.ggufGGUFGGUF8.07 GBDownload
Newton-bot-3-VLM-mini-4B.mmproj-Q8_0.ggufGGUFQ8_0349.9 MBDownload
Newton-bot-3-VLM-mini-4B.mmproj-f16.ggufGGUFF16641.3 MBDownload

Model Details

Model IDmradermacher/Newton-bot-3-VLM-mini-4B-GGUF
Authormradermacher
Pipelineimage-text-to-text
Licensegpl-3.0
Base modelKolyadual/Newton-bot-3-VLM-mini-4B
Last modified2026-06-28T10:30:09.000Z

Model README

---

base_model: Kolyadual/Newton-bot-3-VLM-mini-4B

datasets:

  • TeichAI/gemini-3-flash-preview

language:

  • ru
  • en
  • fr
  • uk
  • be
  • pl

library_name: transformers

license: gpl-3.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • NewtonBotFamilyTree
  • image-text-to-text
  • gemini
  • unsloth

---

About

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

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

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

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

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

<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->

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

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

static quants of https://huggingface.co/Kolyadual/Newton-bot-3-VLM-mini-4B

<!-- provided-files -->

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 | mmproj-Q8_0 | 0.5 | multi-modal supplement |

| GGUF | mmproj-f16 | 0.8 | multi-modal supplement |

| GGUF | Q2_K | 2.1 | |

| GGUF | Q3_K_S | 2.2 | |

| GGUF | Q3_K_M | 2.4 | lower quality |

| GGUF | Q3_K_L | 2.6 | |

| GGUF | IQ4_XS | 2.7 | |

| GGUF | Q4_K_S | 2.7 | fast, recommended |

| GGUF | Q4_K_M | 2.9 | fast, recommended |

| GGUF | Q5_K_S | 3.2 | |

| GGUF | Q5_K_M | 3.3 | |

| GGUF | Q6_K | 3.7 | very good quality |

| GGUF | Q8_0 | 4.7 | fast, best quality |

| GGUF | f16 | 8.8 | 16 bpw, overkill |

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.

<!-- end -->

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