mradermacher/Spaetzle-v61-7b-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/cstr/Spaetzle v61 7b …
Runs locally from ~2.53 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Spaetzle-v61-7b.IQ4_XS.gguf | GGUF | GGUF | 3.67 GB | Download |
| Spaetzle-v61-7b.Q2_K.gguf | GGUF | GGUF | 2.53 GB | Download |
| Spaetzle-v61-7b.Q3_K_L.gguf | GGUF | GGUF | 3.56 GB | Download |
| Spaetzle-v61-7b.Q3_K_M.gguf | GGUF | GGUF | 3.28 GB | Download |
| Spaetzle-v61-7b.Q3_K_S.gguf | GGUF | GGUF | 2.95 GB | Download |
| Spaetzle-v61-7b.Q4_K_M.gguf | GGUF | GGUF | 4.07 GB | Download |
| Spaetzle-v61-7b.Q4_K_S.gguf | GGUF | GGUF | 3.86 GB | Download |
| Spaetzle-v61-7b.Q5_K_M.gguf | GGUF | GGUF | 4.78 GB | Download |
| Spaetzle-v61-7b.Q5_K_S.gguf | GGUF | GGUF | 4.65 GB | Download |
| Spaetzle-v61-7b.Q6_K.gguf | GGUF | GGUF | 5.53 GB | Download |
| Spaetzle-v61-7b.Q8_0.gguf | GGUF | GGUF | 7.17 GB | Download |
| Spaetzle-v61-7b.f16.gguf | GGUF | GGUF | 13.49 GB | Download |
Model Details
| Model ID | mradermacher/Spaetzle-v61-7b-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | apache-2.0 |
| Base model | cstr/Spaetzle-v61-7b |
| Last modified | 2026-09-06T13:18:59.000Z |
Model README
---
base_model: cstr/Spaetzle-v61-7b
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- merge
- mergekit
- lazymergekit
- FelixChao/WestSeverus-7B-DPO-v2
- mayflowergmbh/Wiedervereinigung-7b-dpo
- cognitivecomputations/openchat-3.5-0106-laser
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/cstr/Spaetzle-v61-7b
<!-- 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 | 2.8 | |
| GGUF | Q3_K_S | 3.3 | |
| GGUF | Q3_K_M | 3.6 | lower quality |
| GGUF | Q3_K_L | 3.9 | |
| GGUF | IQ4_XS | 4.0 | |
| GGUF | Q4_K_S | 4.2 | fast, recommended |
| GGUF | Q4_K_M | 4.5 | fast, recommended |
| GGUF | Q5_K_S | 5.1 | |
| GGUF | Q5_K_M | 5.2 | |
| GGUF | Q6_K | 6.0 | very good quality |
| GGUF | Q8_0 | 7.8 | fast, best quality |
| GGUF | f16 | 14.6 | 16 bpw, overkill |
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.
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