---
base_model: ExAi/dolphin-2.9-llama3-MoE-4x70B
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- HuggingFaceH4/ultrachat_200k
- microsoft/orca-math-word-problems-200k
- abacusai/SystemChat-1.1
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
language:
- en
library_name: transformers
license: llama3
quantized_by: mradermacher
---
## About

<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
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<!-- ### tags: nicoboss -->
static quants of https://huggingface.co/ExAi/dolphin-2.9-llama3-MoE-4x70B

<!-- provided-files -->
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/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q2_K.gguf.part2of2) | Q2_K | 87.7 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_S.gguf.part3of3) | Q3_K_S | 103.7 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_M.gguf.part3of3) | Q3_K_M | 115.0 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_L.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_L.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q3_K_L.gguf.part3of3) | Q3_K_L | 124.5 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.IQ4_XS.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.IQ4_XS.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.IQ4_XS.gguf.part3of3) | IQ4_XS | 129.3 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_S.gguf.part3of3) | Q4_K_S | 136.5 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q4_K_M.gguf.part3of3) | Q4_K_M | 145.0 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_S.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_S.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_S.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_S.gguf.part4of4) | Q5_K_S | 165.0 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_M.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_M.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_M.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q5_K_M.gguf.part4of4) | Q5_K_M | 170.1 |  |
| [PART 1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q6_K.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q6_K.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q6_K.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q6_K.gguf.part4of4) | Q6_K | 196.7 | very good quality |
| [P1](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part1of6) [P2](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part2of6) [P3](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part3of6) [P4](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part4of6) [P5](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part5of6) [P6](https://huggingface.co/mradermacher/dolphin-2.9-llama3-MoE-4x70B-GGUF/resolve/main/dolphin-2.9-llama3-MoE-4x70B.Q8_0.gguf.part6of6) | Q8_0 | 254.8 | 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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