GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

mradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-i1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss weighted/imatrix quants of https://huggingface.co/Ke…

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:usimatrixconversational

Runs locally from ~9.15 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
15
Likes
0
Pipeline

Repository Files & Downloads

21 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ1_M.ggufGGUFIQ1_M10.10 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ1_S.ggufGGUFIQ1_S9.15 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ2_M.ggufGGUFIQ2_M14.43 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ2_S.ggufGGUFIQ2_S13.16 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ2_XS.ggufGGUFIQ2_XS12.97 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ2_XXS.ggufGGUFIQ2_XXS11.69 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ3_M.ggufGGUFIQ3_M19.96 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ3_S.ggufGGUFIQ3_S19.03 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ3_XS.ggufGGUFIQ3_XS18.02 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ3_XXS.ggufGGUFIQ3_XXS16.99 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-IQ4_XS.ggufGGUFIQ4_XS23.36 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q2_K.ggufGGUFQ2_K16.12 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q3_K_L.ggufGGUFQ3_K_L22.51 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q3_K_M.ggufGGUFQ3_K_M21.00 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q3_K_S.ggufGGUFQ3_K_S19.03 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q4_0.ggufGGUFQ4_024.74 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q4_K_M.ggufGGUFQ4_K_M26.49 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q4_K_S.ggufGGUFQ4_K_S24.91 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q5_K_M.ggufGGUFQ5_K_M30.95 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q5_K_S.ggufGGUFQ5_K_S30.02 GBDownload
MELT-Mixtral-8x7B-Instruct-v0.1.i1-Q6_K.ggufGGUFQ6_K35.74 GBDownload

Model Details

Model IDmradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelKentucky-Open-Science/MELT-Mixtral-8x7B-Instruct-v0.1
Last modified2026-07-19T22:33:57.000Z

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: nicoboss -->

weighted/imatrix 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.

static quants are available at https://huggingface.co/mradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-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 | i1-IQ1_S | 9.9 | for the desperate |

| GGUF | i1-IQ1_M | 10.9 | mostly desperate |

| GGUF | i1-IQ2_XXS | 12.7 | |

| GGUF | i1-IQ2_XS | 14.0 | |

| GGUF | i1-IQ2_S | 14.2 | |

| GGUF | i1-IQ2_M | 15.6 | |

| GGUF | i1-Q2_K | 17.4 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 18.3 | lower quality |

| GGUF | i1-IQ3_XS | 19.5 | |

| GGUF | i1-IQ3_S | 20.5 | beats Q3_K* |

| GGUF | i1-Q3_K_S | 20.5 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 21.5 | |

| GGUF | i1-Q3_K_M | 22.6 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 24.3 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 25.2 | |

| GGUF | i1-Q4_0 | 26.7 | fast, low quality |

| GGUF | i1-Q4_K_S | 26.8 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 28.5 | fast, recommended |

| GGUF | i1-Q5_K_S | 32.3 | |

| GGUF | i1-Q5_K_M | 33.3 | |

| GGUF | i1-Q6_K | 38.5 | 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 -->

Run mradermacher/MELT-Mixtral-8x7B-Instruct-v0.1-i1-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models