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mradermacher/Mira-1.10-dpo-27B-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…

transformersggufendataset:sam-paech/gutenberg3-generalfiction-scifi-fantasy-romance-adventure-dpodataset:allenai/tulu-3-sft-personas-instruction-followingbase_model:Lambent/Mira-1.10-dpo-27Bbase_model:quantized:Lambent/Mira-1.10-dpo-27Blicense:gemmaendpoints_compatibleregion:usconversational

Runs locally from ~570.2 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Likes
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Pipeline
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Repository Files & Downloads

13 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Mira-1.10-dpo-27B.IQ4_XS.ggufGGUFGGUF13.87 GBDownload
Mira-1.10-dpo-27B.Q2_K.ggufGGUFGGUF9.78 GBDownload
Mira-1.10-dpo-27B.Q3_K_L.ggufGGUFGGUF13.54 GBDownload
Mira-1.10-dpo-27B.Q3_K_M.ggufGGUFGGUF12.51 GBDownload
Mira-1.10-dpo-27B.Q3_K_S.ggufGGUFGGUF11.33 GBDownload
Mira-1.10-dpo-27B.Q4_K_M.ggufGGUFGGUF15.41 GBDownload
Mira-1.10-dpo-27B.Q4_K_S.ggufGGUFGGUF14.60 GBDownload
Mira-1.10-dpo-27B.Q5_K_M.ggufGGUFGGUF17.95 GBDownload
Mira-1.10-dpo-27B.Q5_K_S.ggufGGUFGGUF17.48 GBDownload
Mira-1.10-dpo-27B.Q6_K.ggufGGUFGGUF20.64 GBDownload
Mira-1.10-dpo-27B.Q8_0.ggufGGUFGGUF26.74 GBDownload
Mira-1.10-dpo-27B.mmproj-Q8_0.ggufGGUFQ8_0570.2 MBDownload
Mira-1.10-dpo-27B.mmproj-f16.ggufGGUFF16818.0 MBDownload

Model Details

Model IDmradermacher/Mira-1.10-dpo-27B-GGUF
Authormradermacher
Pipeline—
Licensegemma
Base modelLambent/Mira-1.10-dpo-27B
Last modified2026-10-20T06:27:32.000Z

Model README

---

base_model: Lambent/Mira-1.10-dpo-27B

datasets:

  • sam-paech/gutenberg3-generalfiction-scifi-fantasy-romance-adventure-dpo
  • allenai/tulu-3-sft-personas-instruction-following

language:

  • en

library_name: transformers

license: gemma

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/Lambent/Mira-1.10-dpo-27B

<!-- 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/Mira-1.10-dpo-27B-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 | mmproj-Q8_0 | 0.7 | multi-modal supplement |

| GGUF | mmproj-f16 | 1.0 | multi-modal supplement |

| GGUF | Q2_K | 10.6 | |

| GGUF | Q3_K_S | 12.3 | |

| GGUF | Q3_K_M | 13.5 | lower quality |

| GGUF | Q3_K_L | 14.6 | |

| GGUF | IQ4_XS | 15.0 | |

| GGUF | Q4_K_S | 15.8 | fast, recommended |

| GGUF | Q4_K_M | 16.6 | fast, recommended |

| GGUF | Q5_K_S | 18.9 | |

| GGUF | Q5_K_M | 19.4 | |

| GGUF | Q6_K | 22.3 | very good quality |

| GGUF | Q8_0 | 28.8 | 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. 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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