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mradermacher/Atem-4B-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…

transformersggufunslothloraqwen3reasoningdistillationchain-of-thoughtendataset:mitroitskii/OpenR1-Math-220k-formatteddataset:Jackrong/Claude-opus-4.6-TraceInversion-9000xdataset:Jackrong/Kimi-K2.5-Reasoning-1M-Cleaneddataset:WithinUsAI/MiniMax_M2.7_Distilled_5kdataset:FreedomIntelligence/medical-o1-reasoning-SFTdataset:Modotte/CodeX-2M-Thinkingdataset:trjxter/DeepSeek-V4-Pro-Reasoning-8000xdataset:nvidia/OpenCodeReasoningbase_model:EphAsad/Atem-4Bbase_model:adapter:EphAsad/Atem-4Blicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~3.7 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
Atem-4B.i1-IQ1_M.ggufGGUFIQ1_M1.05 GBDownload
Atem-4B.i1-IQ1_S.ggufGGUFIQ1_S1006.4 MBDownload
Atem-4B.i1-IQ2_M.ggufGGUFIQ2_M1.41 GBDownload
Atem-4B.i1-IQ2_S.ggufGGUFIQ2_S1.32 GBDownload
Atem-4B.i1-IQ2_XS.ggufGGUFIQ2_XS1.26 GBDownload
Atem-4B.i1-IQ2_XXS.ggufGGUFIQ2_XXS1.16 GBDownload
Atem-4B.i1-IQ3_M.ggufGGUFIQ3_M1.83 GBDownload
Atem-4B.i1-IQ3_S.ggufGGUFIQ3_S1.77 GBDownload
Atem-4B.i1-IQ3_XS.ggufGGUFIQ3_XS1.69 GBDownload
Atem-4B.i1-IQ3_XXS.ggufGGUFIQ3_XXS1.56 GBDownload
Atem-4B.i1-IQ4_NL.ggufGGUFIQ4_NL2.22 GBDownload
Atem-4B.i1-IQ4_XS.ggufGGUFIQ4_XS2.11 GBDownload
Atem-4B.i1-Q2_K.ggufGGUFQ2_K1.55 GBDownload
Atem-4B.i1-Q2_K_S.ggufGGUFQ2_K_S1.46 GBDownload
Atem-4B.i1-Q3_K_L.ggufGGUFQ3_K_L2.09 GBDownload
Atem-4B.i1-Q3_K_M.ggufGGUFQ3_K_M1.93 GBDownload
Atem-4B.i1-Q3_K_S.ggufGGUFQ3_K_S1.76 GBDownload
Atem-4B.i1-Q4_0.ggufGGUFQ4_02.21 GBDownload
Atem-4B.i1-Q4_1.ggufGGUFQ4_12.42 GBDownload
Atem-4B.i1-Q4_K_M.ggufGGUFQ4_K_M2.33 GBDownload
Atem-4B.i1-Q4_K_S.ggufGGUFQ4_K_S2.22 GBDownload
Atem-4B.i1-Q5_K_M.ggufGGUFQ5_K_M2.69 GBDownload
Atem-4B.i1-Q5_K_S.ggufGGUFQ5_K_S2.63 GBDownload
Atem-4B.i1-Q6_K.ggufGGUFQ6_K3.08 GBDownload
Atem-4B.imatrix.ggufGGUFGGUF3.7 MBDownload

Model Details

Model IDmradermacher/Atem-4B-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelEphAsad/Atem-4B
Last modified2026-06-23T04:10:27.000Z

Model README

---

base_model: EphAsad/Atem-4B

datasets:

  • mitroitskii/OpenR1-Math-220k-formatted
  • Jackrong/Claude-opus-4.6-TraceInversion-9000x
  • Jackrong/Kimi-K2.5-Reasoning-1M-Cleaned
  • WithinUsAI/MiniMax_M2.7_Distilled_5k
  • FreedomIntelligence/medical-o1-reasoning-SFT
  • Modotte/CodeX-2M-Thinking
  • trjxter/DeepSeek-V4-Pro-Reasoning-8000x
  • nvidia/OpenCodeReasoning

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • unsloth
  • lora
  • qwen3
  • reasoning
  • distillation
  • chain-of-thought

---

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/EphAsad/Atem-4B

<!-- 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/Atem-4B-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 | 1.2 | for the desperate |

| GGUF | i1-IQ1_M | 1.2 | mostly desperate |

| GGUF | i1-IQ2_XXS | 1.3 | |

| GGUF | i1-IQ2_XS | 1.5 | |

| GGUF | i1-IQ2_S | 1.5 | |

| GGUF | i1-IQ2_M | 1.6 | |

| GGUF | i1-Q2_K_S | 1.7 | very low quality |

| GGUF | i1-Q2_K | 1.8 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 1.8 | lower quality |

| GGUF | i1-IQ3_XS | 1.9 | |

| GGUF | i1-Q3_K_S | 2.0 | IQ3_XS probably better |

| GGUF | i1-IQ3_S | 2.0 | beats Q3_K* |

| GGUF | i1-IQ3_M | 2.1 | |

| GGUF | i1-Q3_K_M | 2.2 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 2.3 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 2.4 | |

| GGUF | i1-Q4_0 | 2.5 | fast, low quality |

| GGUF | i1-IQ4_NL | 2.5 | prefer IQ4_XS |

| GGUF | i1-Q4_K_S | 2.5 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 2.6 | fast, recommended |

| GGUF | i1-Q4_1 | 2.7 | |

| GGUF | i1-Q5_K_S | 2.9 | |

| GGUF | i1-Q5_K_M | 3.0 | |

| GGUF | i1-Q6_K | 3.4 | 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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