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mradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-GGUF overview

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

transformersggufenbase_model:Kentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1base_model:quantized:Kentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1license:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~16.12 GB disk (24 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

11 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
MELT-Mixtral-8x7B-Instruct-v0.1.IQ4_XS.ggufGGUFGGUF23.63 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q2_K.ggufGGUFGGUF16.12 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q3_K_L.ggufGGUFGGUF22.51 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q3_K_M.ggufGGUFGGUF21.00 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q3_K_S.ggufGGUFGGUF19.03 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q4_K_M.ggufGGUFGGUF26.49 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q4_K_S.ggufGGUFGGUF24.91 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q5_K_M.ggufGGUFGGUF30.95 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q5_K_S.ggufGGUFGGUF30.02 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q6_K.ggufGGUFGGUF35.74 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.Q8_0.ggufGGUFGGUF46.22 GBDownload

Model Details

Model IDmradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelKentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1
Last modified2026-07-09T14:32:22.000Z

Model README

---

base_model: Kentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

---

About

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

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

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

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

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

static quants of https://huggingface.co/Kentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1

<!-- 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/MELT-Mixtral-8x7B-Instruct-v0.1-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 | 17.4 | |

| GGUF | Q3_K_S | 20.5 | |

| GGUF | Q3_K_M | 22.6 | lower quality |

| GGUF | Q3_K_L | 24.3 | |

| GGUF | IQ4_XS | 25.5 | |

| GGUF | Q4_K_S | 26.8 | fast, recommended |

| GGUF | Q4_K_M | 28.5 | fast, recommended |

| GGUF | Q5_K_S | 32.3 | |

| GGUF | Q5_K_M | 33.3 | |

| GGUF | Q6_K | 38.5 | very good quality |

| GGUF | Q8_0 | 49.7 | 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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