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mradermacher/Trinity-Mini-Base-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…

transformersggufenesfrdeitptruarhikozhbase_model:arcee-ai/Trinity-Mini-Basebase_model:quantized:arcee-ai/Trinity-Mini-Baselicense:otherendpoints_compatibleregion:usconversational

Runs locally from ~9.01 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Pipeline

Repository Files & Downloads

11 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Trinity-Mini-Base.IQ4_XS.ggufGGUFGGUF13.16 GBDownload
Trinity-Mini-Base.Q2_K.ggufGGUFGGUF9.01 GBDownload
Trinity-Mini-Base.Q3_K_L.ggufGGUFGGUF12.66 GBDownload
Trinity-Mini-Base.Q3_K_M.ggufGGUFGGUF11.68 GBDownload
Trinity-Mini-Base.Q3_K_S.ggufGGUFGGUF10.64 GBDownload
Trinity-Mini-Base.Q4_K_M.ggufGGUFGGUF14.74 GBDownload
Trinity-Mini-Base.Q4_K_S.ggufGGUFGGUF13.88 GBDownload
Trinity-Mini-Base.Q5_K_M.ggufGGUFGGUF17.28 GBDownload
Trinity-Mini-Base.Q5_K_S.ggufGGUFGGUF16.81 GBDownload
Trinity-Mini-Base.Q6_K.ggufGGUFGGUF19.99 GBDownload
Trinity-Mini-Base.Q8_0.ggufGGUFGGUF25.88 GBDownload

Model Details

Model IDmradermacher/Trinity-Mini-Base-GGUF
Authormradermacher
Pipeline
Licenseother
Base modelarcee-ai/Trinity-Mini-Base
Last modified2026-06-23T18:47:05.000Z

Model README

---

base_model: arcee-ai/Trinity-Mini-Base

language:

  • en
  • es
  • fr
  • de
  • it
  • pt
  • ru
  • ar
  • hi
  • ko
  • zh

library_name: transformers

license: other

license_link: LICENSE

license_name: openmdw-1.1

mradermacher:

readme_rev: 1

quantized_by: mradermacher

---

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/arcee-ai/Trinity-Mini-Base

<!-- 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/Trinity-Mini-Base-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 | 9.8 | |

| GGUF | Q3_K_S | 11.5 | |

| GGUF | Q3_K_M | 12.6 | lower quality |

| GGUF | Q3_K_L | 13.7 | |

| GGUF | IQ4_XS | 14.2 | |

| GGUF | Q4_K_S | 15.0 | fast, recommended |

| GGUF | Q4_K_M | 15.9 | fast, recommended |

| GGUF | Q5_K_S | 18.1 | |

| GGUF | Q5_K_M | 18.7 | |

| GGUF | Q6_K | 21.6 | very good quality |

| GGUF | Q8_0 | 27.9 | 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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