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mradermacher/Qwen3-Coder-Next-REAM-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…

transformersggufcompressionexpert-mergingmoecodeenbase_model:bknyaz/Qwen3-Coder-Next-REAMbase_model:quantized:bknyaz/Qwen3-Coder-Next-REAMlicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~327.8 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Repository Files & Downloads

24 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3-Coder-Next-REAM.i1-IQ1_M.ggufGGUFIQ1_M12.93 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ1_S.ggufGGUFIQ1_S11.67 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ2_M.ggufGGUFIQ2_M18.55 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ2_S.ggufGGUFIQ2_S16.87 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ2_XS.ggufGGUFIQ2_XS16.71 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ2_XXS.ggufGGUFIQ2_XXS15.03 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ3_M.ggufGGUFIQ3_M24.78 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ3_S.ggufGGUFIQ3_S24.47 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ3_XS.ggufGGUFIQ3_XS23.19 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ3_XXS.ggufGGUFIQ3_XXS21.85 GBDownload
Qwen3-Coder-Next-REAM.i1-IQ4_XS.ggufGGUFIQ4_XS30.16 GBDownload
Qwen3-Coder-Next-REAM.i1-Q2_K.ggufGGUFQ2_K20.70 GBDownload
Qwen3-Coder-Next-REAM.i1-Q2_K_S.ggufGGUFQ2_K_S19.38 GBDownload
Qwen3-Coder-Next-REAM.i1-Q3_K_L.ggufGGUFQ3_K_L29.22 GBDownload
Qwen3-Coder-Next-REAM.i1-Q3_K_M.ggufGGUFQ3_K_M27.02 GBDownload
Qwen3-Coder-Next-REAM.i1-Q3_K_S.ggufGGUFQ3_K_S24.39 GBDownload
Qwen3-Coder-Next-REAM.i1-Q4_0.ggufGGUFQ4_031.95 GBDownload
Qwen3-Coder-Next-REAM.i1-Q4_1.ggufGGUFQ4_135.30 GBDownload
Qwen3-Coder-Next-REAM.i1-Q4_K_M.ggufGGUFQ4_K_M34.21 GBDownload
Qwen3-Coder-Next-REAM.i1-Q4_K_S.ggufGGUFQ4_K_S32.10 GBDownload
Qwen3-Coder-Next-REAM.i1-Q5_K_M.ggufGGUFQ5_K_M40.03 GBDownload
Qwen3-Coder-Next-REAM.i1-Q5_K_S.ggufGGUFQ5_K_S38.80 GBDownload
Qwen3-Coder-Next-REAM.i1-Q6_K.ggufGGUFQ6_K46.22 GBDownload
Qwen3-Coder-Next-REAM.imatrix.ggufGGUFGGUF327.8 MBDownload

Model Details

Model IDmradermacher/Qwen3-Coder-Next-REAM-i1-GGUF
Authormradermacher
Pipeline
Licenseapache-2.0
Base modelbknyaz/Qwen3-Coder-Next-REAM
Last modified2026-07-10T08:02:54.000Z

Model README

---

base_model: bknyaz/Qwen3-Coder-Next-REAM

language:

  • en

library_name: transformers

license: apache-2.0

mradermacher:

readme_rev: 1

quantized_by: mradermacher

tags:

  • compression
  • expert-merging
  • moe
  • code

---

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/bknyaz/Qwen3-Coder-Next-REAM

<!-- 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/Qwen3-Coder-Next-REAM-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 | 0.4 | imatrix file (for creating your own quants) |

| GGUF | i1-IQ1_S | 12.6 | for the desperate |

| GGUF | i1-IQ1_M | 14.0 | mostly desperate |

| GGUF | i1-IQ2_XXS | 16.2 | |

| GGUF | i1-IQ2_XS | 18.0 | |

| GGUF | i1-IQ2_S | 18.2 | |

| GGUF | i1-IQ2_M | 20.0 | |

| GGUF | i1-Q2_K_S | 20.9 | very low quality |

| GGUF | i1-Q2_K | 22.3 | IQ3_XXS probably better |

| GGUF | i1-IQ3_XXS | 23.6 | lower quality |

| GGUF | i1-IQ3_XS | 25.0 | |

| GGUF | i1-Q3_K_S | 26.3 | IQ3_XS probably better |

| GGUF | i1-IQ3_S | 26.4 | beats Q3_K* |

| GGUF | i1-IQ3_M | 26.7 | |

| GGUF | i1-Q3_K_M | 29.1 | IQ3_S probably better |

| GGUF | i1-Q3_K_L | 31.5 | IQ3_M probably better |

| GGUF | i1-IQ4_XS | 32.5 | |

| GGUF | i1-Q4_0 | 34.4 | fast, low quality |

| GGUF | i1-Q4_K_S | 34.6 | optimal size/speed/quality |

| GGUF | i1-Q4_K_M | 36.8 | fast, recommended |

| GGUF | i1-Q4_1 | 38.0 | |

| GGUF | i1-Q5_K_S | 41.8 | |

| GGUF | i1-Q5_K_M | 43.1 | |

| GGUF | i1-Q6_K | 49.7 | 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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