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mradermacher/BlazerNano-V2-Again-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:Davizig10jojo/BlazerNano_V2dataset:Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Datasetdataset:Polygl0t/gigaverbo-v2-sftbase_model:Davizig10jojo/BlazerNano-V2-Againbase_model:quantized:Davizig10jojo/BlazerNano-V2-Againendpoints_compatibleregion:usconversational

Runs locally from ~331.2 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

12 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
BlazerNano-V2-Again.IQ4_XS.ggufGGUFGGUF431.0 MBDownload
BlazerNano-V2-Again.Q2_K.ggufGGUFGGUF331.2 MBDownload
BlazerNano-V2-Again.Q3_K_L.ggufGGUFGGUF415.2 MBDownload
BlazerNano-V2-Again.Q3_K_M.ggufGGUFGGUF394.8 MBDownload
BlazerNano-V2-Again.Q3_K_S.ggufGGUFGGUF371.9 MBDownload
BlazerNano-V2-Again.Q4_K_M.ggufGGUFGGUF461.8 MBDownload
BlazerNano-V2-Again.Q4_K_S.ggufGGUFGGUF449.0 MBDownload
BlazerNano-V2-Again.Q5_K_M.ggufGGUFGGUF525.8 MBDownload
BlazerNano-V2-Again.Q5_K_S.ggufGGUFGGUF518.4 MBDownload
BlazerNano-V2-Again.Q6_K.ggufGGUFGGUF593.9 MBDownload
BlazerNano-V2-Again.Q8_0.ggufGGUFGGUF767.5 MBDownload
BlazerNano-V2-Again.f16.ggufGGUFGGUF1.41 GBDownload

Model Details

Model IDmradermacher/BlazerNano-V2-Again-GGUF
Authormradermacher
Pipeline
License
Base modelDavizig10jojo/BlazerNano-V2-Again
Last modified2026-08-04T18:00:00.000Z

Model README

---

base_model: Davizig10jojo/BlazerNano-V2-Again

datasets:

  • Davizig10jojo/BlazerNano_V2
  • Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
  • Polygl0t/gigaverbo-v2-sft

language:

  • en

library_name: transformers

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/Davizig10jojo/BlazerNano-V2-Again

<!-- 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 | 0.4 | |

| GGUF | Q3_K_S | 0.5 | |

| GGUF | Q3_K_M | 0.5 | lower quality |

| GGUF | Q3_K_L | 0.5 | |

| GGUF | IQ4_XS | 0.6 | |

| GGUF | Q4_K_S | 0.6 | fast, recommended |

| GGUF | Q4_K_M | 0.6 | fast, recommended |

| GGUF | Q5_K_S | 0.6 | |

| GGUF | Q5_K_M | 0.7 | |

| GGUF | Q6_K | 0.7 | very good quality |

| GGUF | Q8_0 | 0.9 | fast, best quality |

| GGUF | f16 | 1.6 | 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.

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