---
base_model:
- 152334H/miqu-1-70b-sf
- lizpreciatior/lzlv_70b_fp16_hf
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About

static quants of https://huggingface.co/wolfram/miquliz-120b-v2.0

While other static and imatrix quants are available already, I wanted a wider selection of quants available for this model.

<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/miquliz-120b-v2.0-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](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q2_K.gguf) | Q2_K | 44.6 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_XS.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_XS.gguf.split-ab) | Q3_K_XS | 49.3 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_S.gguf.split-ab) | Q3_K_S | 52.2 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_M.gguf.split-ab) | Q3_K_M | 58.2 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_L.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q3_K_L.gguf.split-ab) | Q3_K_L | 63.4 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q4_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q4_K_S.gguf.split-ab) | Q4_K_S | 68.7 | fast, medium quality |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.IQ4_NL.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.IQ4_NL.gguf.split-ab) | IQ4_NL | 68.8 | fast, slightly worse than Q4_K_S |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q4_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q4_K_M.gguf.split-ab) | Q4_K_M | 72.6 | fast, medium quality |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q5_K_S.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q5_K_S.gguf.split-ab) | Q5_K_S | 83.2 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q5_K_M.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q5_K_M.gguf.split-ab) | Q5_K_M | 85.4 |  |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q6_K.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q6_K.gguf.split-ab) [PART 3](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q6_K.gguf.split-ac) | Q6_K | 99.1 | very good quality |
| [PART 1](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q8_0.gguf.split-aa) [PART 2](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q8_0.gguf.split-ab) [PART 3](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF/resolve/main/miquliz-120b-v2.0.Q8_0.gguf.split-ac) | Q8_0 | 128.2 | fast, best quality |


Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

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