---
base_model: NousResearch/Hermes-3-Llama-3.1-405B
language:
- en
library_name: transformers
license: llama3
quantized_by: mradermacher
tags:
- Llama-3
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- distillation
- function calling
- json mode
- axolotl
- roleplaying
- chat
---
## About

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static quants of https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-405B

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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/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.IQ3_S.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.IQ3_S.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.IQ3_S.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.IQ3_S.gguf.part4of4) | IQ3_S | 175.6 | beats Q3_K* |
| [P1](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q4_K_S.gguf.part1of5) [P2](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q4_K_S.gguf.part2of5) [P3](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q4_K_S.gguf.part3of5) [P4](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q4_K_S.gguf.part4of5) [P5](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q4_K_S.gguf.part5of5) | Q4_K_S | 230.6 | fast, recommended |
| [P1](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part1of9) [P2](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part2of9) [P3](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part3of9) [P4](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part4of9) [P5](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part5of9) [P6](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part6of9) [P7](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part7of9) [P8](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part8of9) [P9](https://huggingface.co/mradermacher/Hermes-3-Llama-3.1-405B-GGUF/resolve/main/Hermes-3-Llama-3.1-405B.Q8_0.gguf.part9of9) | Q8_0 | 431.3 | 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. Additional thanks to [@nicoboss](https://huggingface.co/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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