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mradermacher/granite-4.0-h-3b-ar-i1-GGUF overview

About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss < quants: Q2 K IQ3 M Q4 K S IQ3 XXS Q3 K M small IQ4…

transformersggufenaracmapcarsaryarzafbbase_model:ibm-research/granite-4.0-h-3b-arbase_model:quantized:ibm-research/granite-4.0-h-3b-arlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~2.9 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

25 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
granite-4.0-h-3b-ar.i1-IQ1_M.ggufGGUFIQ1_M839.2 MBDownload
granite-4.0-h-3b-ar.i1-IQ1_S.ggufGGUFIQ1_S774.8 MBDownload
granite-4.0-h-3b-ar.i1-IQ2_M.ggufGGUFIQ2_M1.12 GBDownload
granite-4.0-h-3b-ar.i1-IQ2_S.ggufGGUFIQ2_S1.04 GBDownload
granite-4.0-h-3b-ar.i1-IQ2_XS.ggufGGUFIQ2_XS1.01 GBDownload
granite-4.0-h-3b-ar.i1-IQ2_XXS.ggufGGUFIQ2_XXS946.5 MBDownload
granite-4.0-h-3b-ar.i1-IQ3_M.ggufGGUFIQ3_M1.45 GBDownload
granite-4.0-h-3b-ar.i1-IQ3_S.ggufGGUFIQ3_S1.44 GBDownload
granite-4.0-h-3b-ar.i1-IQ3_XS.ggufGGUFIQ3_XS1.40 GBDownload
granite-4.0-h-3b-ar.i1-IQ3_XXS.ggufGGUFIQ3_XXS1.28 GBDownload
granite-4.0-h-3b-ar.i1-IQ4_NL.ggufGGUFIQ4_NL1.84 GBDownload
granite-4.0-h-3b-ar.i1-IQ4_XS.ggufGGUFIQ4_XS1.74 GBDownload
granite-4.0-h-3b-ar.i1-Q2_K.ggufGGUFQ2_K1.20 GBDownload
granite-4.0-h-3b-ar.i1-Q2_K_S.ggufGGUFQ2_K_S1.16 GBDownload
granite-4.0-h-3b-ar.i1-Q3_K_L.ggufGGUFQ3_K_L1.61 GBDownload
granite-4.0-h-3b-ar.i1-Q3_K_M.ggufGGUFQ3_K_M1.53 GBDownload
granite-4.0-h-3b-ar.i1-Q3_K_S.ggufGGUFQ3_K_S1.44 GBDownload
granite-4.0-h-3b-ar.i1-Q4_0.ggufGGUFQ4_01.84 GBDownload
granite-4.0-h-3b-ar.i1-Q4_1.ggufGGUFQ4_12.02 GBDownload
granite-4.0-h-3b-ar.i1-Q4_K_M.ggufGGUFQ4_K_M1.92 GBDownload
granite-4.0-h-3b-ar.i1-Q4_K_S.ggufGGUFQ4_K_S1.85 GBDownload
granite-4.0-h-3b-ar.i1-Q5_K_M.ggufGGUFQ5_K_M2.25 GBDownload
granite-4.0-h-3b-ar.i1-Q5_K_S.ggufGGUFQ5_K_S2.21 GBDownload
granite-4.0-h-3b-ar.i1-Q6_K.ggufGGUFQ6_K2.60 GBDownload
granite-4.0-h-3b-ar.imatrix.ggufGGUFGGUF2.9 MBDownload

Model Details

Model IDmradermacher/granite-4.0-h-3b-ar-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelibm-research/granite-4.0-h-3b-ar
Last modified2026-07-01T15:36:39.000Z

Model README

---

base_model: ibm-research/granite-4.0-h-3b-ar

language:

  • en
  • ar
  • acm
  • apc
  • ars
  • ary
  • arz
  • afb

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 -->

<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->

<!-- ### quants_skip: -->

<!-- ### skip_mmproj: -->

weighted/imatrix quants of https://huggingface.co/ibm-research/granite-4.0-h-3b-ar

<!-- 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/granite-4.0-h-3b-ar-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 | imatrix | 0.1 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 0.9 | for the desperate |

| GGUF | i1-IQ1_M | 1.0 | mostly desperate |

| GGUF | i1-IQ2_XXS | 1.1 | |

| GGUF | i1-IQ2_XS | 1.2 | |

| GGUF | i1-IQ2_S | 1.2 | |

| GGUF | i1-IQ2_M | 1.3 | |

| GGUF | i1-Q2_K_S | 1.3 | very low quality |

| GGUF | i1-Q2_K | 1.4 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 1.5 | lower quality |

| GGUF | i1-IQ3_XS | 1.6 | |

| GGUF | i1-IQ3_S | 1.6 | beats Q3_K* |

| GGUF | i1-Q3_K_S | 1.6 | IQ3_XS probably better |

| GGUF | i1-IQ3_M | 1.7 | |

| GGUF | i1-Q3_K_M | 1.7 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 1.8 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 2.0 | |

| GGUF | i1-IQ4_NL | 2.1 | prefer IQ4_XS |

| GGUF | i1-Q4_0 | 2.1 | fast, low quality |

| GGUF | i1-Q4_K_S | 2.1 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 2.2 | fast, recommended |

| GGUF | i1-Q4_1 | 2.3 | |

| GGUF | i1-Q5_K_S | 2.5 | |

| GGUF | i1-Q5_K_M | 2.5 | |

| GGUF | i1-Q6_K | 2.9 | 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 -->

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