Transformers
GGUF
programming
code generation
code
codeqwen
Mixture of Experts
coding
coder
qwen2
chat
qwen
qwen-coder
Qwen3-30B-A3B-Instruct-2507
Qwen3-30B-A3B
mixture of experts
128 experts
8 active experts
qwen3
finetune
brainstorm 40x
brainstorm
optional thinking
qwen3_moe
256k context
conversational
auto-patch README.md
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README.md
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/DavidAU/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER
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---
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base_model: DavidAU/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER
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language:
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- en
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- fr
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- zh
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- de
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library_name: transformers
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license: apache-2.0
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- programming
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- code generation
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- code
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- codeqwen
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- programming
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- code generation
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- code
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- codeqwen
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- moe
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- coding
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- coder
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- qwen2
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- chat
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- qwen
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- qwen-coder
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- chat
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- qwen
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- qwen-coder
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- moe
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- Qwen3-30B-A3B-Instruct-2507
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- Qwen3-30B-A3B
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- mixture of experts
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- 128 experts
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- 8 active experts
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- qwen3
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- finetune
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- brainstorm 40x
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- brainstorm
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- optional thinking
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- qwen3_moe
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/DavidAU/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF).***
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-i1-GGUF
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q2_K.gguf) | Q2_K | 19.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q3_K_S.gguf) | Q3_K_S | 23.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q3_K_M.gguf) | Q3_K_M | 25.5 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q3_K_L.gguf) | Q3_K_L | 27.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q4_K_S.gguf) | Q4_K_S | 30.3 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q4_K_M.gguf) | Q4_K_M | 32.2 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q5_K_S.gguf) | Q5_K_S | 36.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q6_K.gguf) | Q6_K | 43.6 | very good quality |
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| [PART 1](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER-GGUF/resolve/main/Qwen3-53B-A3B-2507-TOTAL-RECALL-v2-MASTER-CODER.Q8_0.gguf.part2of2) | Q8_0 | 56.4 | fast, best quality |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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