README.md

---
base_model: DavidAU/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL
language:
- en
- fr
- zh
- de
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- programming
- code generation
- code
- codeqwen
- programming
- code generation
- code
- codeqwen
- moe
- coding
- coder
- qwen2
- chat
- qwen
- qwen-coder
- chat
- qwen
- qwen-coder
- moe
- Qwen3-Coder-30B-A3B-Instruct
- Qwen3-30B-A3B
- mixture of experts
- 128 experts
- 8 active experts
- 1 million context
- qwen3
- finetune
- brainstorm 40x
- brainstorm
- optional thinking
- qwen3_moe
---
## About

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static quants of https://huggingface.co/DavidAU/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF).***

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 |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q2_K.gguf) | Q2_K | 19.5 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q3_K_S.gguf) | Q3_K_S | 23.1 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q3_K_M.gguf) | Q3_K_M | 25.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q3_K_L.gguf) | Q3_K_L | 27.6 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q4_K_S.gguf) | Q4_K_S | 30.3 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q4_K_M.gguf) | Q4_K_M | 32.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q6_K.gguf) | Q6_K | 43.6 | very good quality |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL-GGUF/resolve/main/Qwen3-Yoyo-V3-54B-A3B-Thinking-TOTAL-RECALL.Q8_0.gguf.part2of2) | Q8_0 | 56.4 | 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.

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