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mradermacher/Le-Chaton-Slim-23B-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…

transformersggufmoemixtralmergekitagentictool-callingcodingpythoncode-reasoningcode-editingfunction-callingsmolencodebase_model:HavocK1/Le-Chaton-Slim-23Bbase_model:quantized:HavocK1/Le-Chaton-Slim-23Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~8.06 GB disk (12 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
Le-Chaton-Slim-23B.IQ4_XS.ggufGGUFGGUF11.78 GBDownload
Le-Chaton-Slim-23B.Q2_K.ggufGGUFGGUF8.06 GBDownload
Le-Chaton-Slim-23B.Q3_K_L.ggufGGUFGGUF11.35 GBDownload
Le-Chaton-Slim-23B.Q3_K_M.ggufGGUFGGUF10.48 GBDownload
Le-Chaton-Slim-23B.Q3_K_S.ggufGGUFGGUF9.48 GBDownload
Le-Chaton-Slim-23B.Q4_K_M.ggufGGUFGGUF13.21 GBDownload
Le-Chaton-Slim-23B.Q4_K_S.ggufGGUFGGUF12.42 GBDownload
Le-Chaton-Slim-23B.Q5_K_M.ggufGGUFGGUF15.44 GBDownload
Le-Chaton-Slim-23B.Q5_K_S.ggufGGUFGGUF14.98 GBDownload
Le-Chaton-Slim-23B.Q6_K.ggufGGUFGGUF17.81 GBDownload
Le-Chaton-Slim-23B.Q8_0.ggufGGUFGGUF23.07 GBDownload

Model Details

Model IDmradermacher/Le-Chaton-Slim-23B-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelHavocK1/Le-Chaton-Slim-23B
Last modified2026-07-05T16:11:29.000Z

Model README

---

base_model: HavocK1/Le-Chaton-Slim-23B

language:

  • en
  • code

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • moe
  • mixtral
  • mergekit
  • agentic
  • tool-calling
  • coding
  • python
  • code-reasoning
  • code-editing
  • function-calling
  • smol

---

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/HavocK1/Le-Chaton-Slim-23B

<!-- 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/Le-Chaton-Slim-23B-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 | 8.8 | |

| GGUF | Q3_K_S | 10.3 | |

| GGUF | Q3_K_M | 11.4 | lower quality |

| GGUF | Q3_K_L | 12.3 | |

| GGUF | IQ4_XS | 12.8 | |

| GGUF | Q4_K_S | 13.4 | fast, recommended |

| GGUF | Q4_K_M | 14.3 | fast, recommended |

| GGUF | Q5_K_S | 16.2 | |

| GGUF | Q5_K_M | 16.7 | |

| GGUF | Q6_K | 19.2 | very good quality |

| GGUF | Q8_0 | 24.9 | 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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