--- base_model: dataautogpt3/miqu-120b language: - en library_name: transformers quantized_by: mradermacher tags: - mergekit - merge --- ## About static quants of https://huggingface.co/dataautogpt3/miqu-120b 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 | |:-----|:-----|--------:|:------| | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q2_K.gguf.part2of2) | Q2_K | 50.9 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_XS.gguf.part2of2) | IQ3_XS | 56.4 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_S.gguf.part2of2) | Q3_K_S | 59.6 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_S.gguf.part2of2) | IQ3_S | 59.8 | beats Q3_K* | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ3_M.gguf.part2of2) | IQ3_M | 61.8 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_M.gguf.part2of2) | Q3_K_M | 66.5 | lower quality | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q3_K_L.gguf.part2of2) | Q3_K_L | 72.4 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.IQ4_XS.gguf.part2of2) | IQ4_XS | 74.4 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q4_K_S.gguf.part2of2) | Q4_K_S | 78.4 | fast, recommended | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q4_K_M.gguf.part2of2) | Q4_K_M | 82.8 | fast, recommended | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q5_K_S.gguf.part2of2) | Q5_K_S | 94.9 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q5_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q5_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q5_K_M.gguf.part3of3) | Q5_K_M | 97.5 | | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q6_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q6_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q6_K.gguf.part3of3) | Q6_K | 113.2 | very good quality | | [PART 1](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q8_0.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q8_0.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q8_0.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/miqu-120b-GGUF/resolve/main/miqu-120b.Q8_0.gguf.part4of4) | Q8_0 | 146.4 | 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 ## 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](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.