---
base_model: DavidAU/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B
language:
- en
- fr
- de
- es
- pt
- it
- ja
- ko
- ru
- zh
- ar
- fa
- id
- ms
- ne
- pl
- ro
- sr
- sv
- tr
- uk
- vi
- hi
- bn
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- all use cases
- creative
- creative writing
- all genres
- tool calls
- tool use
- llama 3.1
- llama-3
- llama3
- llama-3.1
- problem solving
- deep thinking
- reasoning
- deep reasoning
- story
- writing
- fiction
- roleplaying
- bfloat16
- role play
- sillytavern
- backyard
- llama 3.1
- context 128k
- mergekit
- merge
- moe
- mixture of experts
---
## About

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static quants of https://huggingface.co/DavidAU/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF).***

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-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/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q2_K.gguf) | Q2_K | 9.4 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q3_K_S.gguf) | Q3_K_S | 11.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q3_K_M.gguf) | Q3_K_M | 12.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q3_K_L.gguf) | Q3_K_L | 13.1 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.IQ4_XS.gguf) | IQ4_XS | 13.7 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q4_K_S.gguf) | Q4_K_S | 14.4 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q4_K_M.gguf) | Q4_K_M | 15.3 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q5_K_S.gguf) | Q5_K_S | 17.3 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q5_K_M.gguf) | Q5_K_M | 17.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q6_K.gguf) | Q6_K | 20.6 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B-GGUF/resolve/main/Llama3.1-MOE-4X8B-Gated-IQ-Multi-Tier-Deep-Reasoning-32B.Q8_0.gguf) | Q8_0 | 26.6 | 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.

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