mradermacher/MachiNoDolphin-Qwen2.5-72b-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss static quants of https://huggingface.co/KaraKaraWare…
Runs locally from ~27.76 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| MachiNoDolphin-Qwen2.5-72b.IQ4_XS.gguf | GGUF | GGUF | 37.40 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q2_K.gguf | GGUF | GGUF | 27.76 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q3_K_L.gguf | GGUF | GGUF | 36.79 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q3_K_M.gguf | GGUF | GGUF | 35.11 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q3_K_S.gguf | GGUF | GGUF | 32.12 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q4_K_M.gguf | GGUF | GGUF | 44.16 GB | Download |
| MachiNoDolphin-Qwen2.5-72b.Q4_K_S.gguf | GGUF | GGUF | 40.88 GB | Download |
Model Details
| Model ID | mradermacher/MachiNoDolphin-Qwen2.5-72b-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | — |
| Base model | KaraKaraWarehouse/MachiNoDolphin-Qwen2.5-72b |
| Last modified | 2026-08-20T03:09:35.000Z |
Model README
---
base_model: KaraKaraWarehouse/MachiNoDolphin-Qwen2.5-72b
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
library_name: transformers
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- mergekit
- merge
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
static quants of https://huggingface.co/KaraKaraWarehouse/MachiNoDolphin-Qwen2.5-72b
<!-- 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/MachiNoDolphin-Qwen2.5-72b-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 | 29.9 | |
| GGUF | Q3_K_S | 34.6 | |
| GGUF | Q3_K_M | 37.8 | lower quality |
| GGUF | Q3_K_L | 39.6 | |
| GGUF | IQ4_XS | 40.3 | |
| GGUF | Q4_K_S | 44.0 | fast, recommended |
| GGUF | Q4_K_M | 47.5 | fast, recommended |
| PART 1 PART 2 | Q5_K_S | 51.5 | |
| PART 1 PART 2 | Q5_K_M | 54.5 | |
| PART 1 PART 2 | Q6_K | 64.4 | very good quality |
| PART 1 PART 2 | Q8_0 | 77.4 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
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.
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