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mradermacher/FalconMind3b-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/devnull37/FalconMind3…

transformersggufautotraintext-generationpeftchain-of-thoughtfinetunedenbase_model:devnull37/FalconMind3bbase_model:quantized:devnull37/FalconMind3bendpoints_compatibleregion:usconversational

Runs locally from ~1.26 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Likes
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Pipeline
text-generation

Repository Files & Downloads

12 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
FalconMind3b.IQ4_XS.ggufGGUFGGUF1.72 GBDownload
FalconMind3b.Q2_K.ggufGGUFGGUF1.26 GBDownload
FalconMind3b.Q3_K_L.ggufGGUFGGUF1.66 GBDownload
FalconMind3b.Q3_K_M.ggufGGUFGGUF1.56 GBDownload
FalconMind3b.Q3_K_S.ggufGGUFGGUF1.44 GBDownload
FalconMind3b.Q4_K_M.ggufGGUFGGUF1.87 GBDownload
FalconMind3b.Q4_K_S.ggufGGUFGGUF1.80 GBDownload
FalconMind3b.Q5_K_M.ggufGGUFGGUF2.16 GBDownload
FalconMind3b.Q5_K_S.ggufGGUFGGUF2.12 GBDownload
FalconMind3b.Q6_K.ggufGGUFGGUF2.47 GBDownload
FalconMind3b.Q8_0.ggufGGUFGGUF3.20 GBDownload
FalconMind3b.f16.ggufGGUFGGUF6.02 GBDownload

Model Details

Model IDmradermacher/FalconMind3b-GGUF
Authormradermacher
Pipelinetext-generation
License
Base modeldevnull37/FalconMind3b
Last modified2026-06-28T14:21:34.000Z

Model README

---

base_model: devnull37/FalconMind3b

language:

  • en

library_name: transformers

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • autotrain
  • text-generation
  • peft
  • chain-of-thought
  • finetuned

---

About

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

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

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

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

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

static quants of https://huggingface.co/devnull37/FalconMind3b

<!-- 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 | Q2_K | 1.5 | |

| GGUF | Q3_K_S | 1.6 | |

| GGUF | Q3_K_M | 1.8 | lower quality |

| GGUF | Q3_K_L | 1.9 | |

| GGUF | IQ4_XS | 1.9 | |

| GGUF | Q4_K_S | 2.0 | fast, recommended |

| GGUF | Q4_K_M | 2.1 | fast, recommended |

| GGUF | Q5_K_S | 2.4 | |

| GGUF | Q5_K_M | 2.4 | |

| GGUF | Q6_K | 2.8 | very good quality |

| GGUF | Q8_0 | 3.5 | fast, best quality |

| GGUF | f16 | 6.6 | 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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