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mradermacher/Proximus-2x7B-v1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/preemware/Proximus 2x…

transformersggufmoemergemergekitlazymergekitbeowolx/MistralHermes-CodePro-7B-v1preemware/Prox-MistralHermes-7Benbase_model:preemware/Proximus-2x7B-v1base_model:quantized:preemware/Proximus-2x7B-v1license:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~4.43 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Likes
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Pipeline

Repository Files & Downloads

14 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Proximus-2x7B-v1.IQ3_M.ggufGGUFGGUF5.35 GBDownload
Proximus-2x7B-v1.IQ3_S.ggufGGUFGGUF5.22 GBDownload
Proximus-2x7B-v1.IQ3_XS.ggufGGUFGGUF4.95 GBDownload
Proximus-2x7B-v1.IQ4_XS.ggufGGUFGGUF6.50 GBDownload
Proximus-2x7B-v1.Q2_K.ggufGGUFGGUF4.43 GBDownload
Proximus-2x7B-v1.Q3_K_L.ggufGGUFGGUF6.27 GBDownload
Proximus-2x7B-v1.Q3_K_M.ggufGGUFGGUF5.78 GBDownload
Proximus-2x7B-v1.Q3_K_S.ggufGGUFGGUF5.20 GBDownload
Proximus-2x7B-v1.Q4_K_M.ggufGGUFGGUF7.25 GBDownload
Proximus-2x7B-v1.Q4_K_S.ggufGGUFGGUF6.84 GBDownload
Proximus-2x7B-v1.Q5_K_M.ggufGGUFGGUF8.51 GBDownload
Proximus-2x7B-v1.Q5_K_S.ggufGGUFGGUF8.26 GBDownload
Proximus-2x7B-v1.Q6_K.ggufGGUFGGUF9.84 GBDownload
Proximus-2x7B-v1.Q8_0.ggufGGUFGGUF12.75 GBDownload

Model Details

Model IDmradermacher/Proximus-2x7B-v1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelpreemware/Proximus-2x7B-v1
Last modified2026-09-05T05:18:52.000Z

Model README

---

base_model: preemware/Proximus-2x7B-v1

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • moe
  • merge
  • mergekit
  • lazymergekit
  • beowolx/MistralHermes-CodePro-7B-v1
  • preemware/Prox-MistralHermes-7B

---

About

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

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

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

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

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

static quants of https://huggingface.co/preemware/Proximus-2x7B-v1

<!-- provided-files -->

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Proximus-2x7B-v1-i1-GGUF

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 | Q2_K | 4.9 | |

| GGUF | IQ3_XS | 5.4 | |

| GGUF | Q3_K_S | 5.7 | |

| GGUF | IQ3_S | 5.7 | beats Q3_K* |

| GGUF | IQ3_M | 5.8 | |

| GGUF | Q3_K_M | 6.3 | lower quality |

| GGUF | Q3_K_L | 6.8 | |

| GGUF | IQ4_XS | 7.1 | |

| GGUF | Q4_K_S | 7.4 | fast, recommended |

| GGUF | Q4_K_M | 7.9 | fast, recommended |

| GGUF | Q5_K_S | 9.0 | |

| GGUF | Q5_K_M | 9.2 | |

| GGUF | Q6_K | 10.7 | very good quality |

| GGUF | Q8_0 | 13.8 | fast, best quality |

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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