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---
base_model: Qwen/Qwen3-235B-A22B-Thinking-2507
language:
- en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507/blob/main/LICENSE
mradermacher:
readme_rev: 1
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static quants of https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507
<!-- provided-files -->
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3-235B-A22B-Thinking-2507-GGUF).***
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-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 |
|:-----|:-----|--------:|:------|
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q2_K.gguf.part2of2) | Q2_K | 85.8 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_S.gguf.part3of3) | Q3_K_S | 101.5 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_M.gguf.part3of3) | Q3_K_M | 112.5 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_L.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_L.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q3_K_L.gguf.part3of3) | Q3_K_L | 121.9 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.IQ4_XS.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.IQ4_XS.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.IQ4_XS.gguf.part3of3) | IQ4_XS | 126.8 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_S.gguf.part3of3) | Q4_K_S | 133.8 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q4_K_M.gguf.part3of3) | Q4_K_M | 142.3 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_S.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_S.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_S.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_S.gguf.part4of4) | Q5_K_S | 162.0 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_M.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_M.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_M.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q5_K_M.gguf.part4of4) | Q5_K_M | 166.9 | |
| [PART 1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q6_K.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q6_K.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q6_K.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q6_K.gguf.part4of4) | Q6_K | 193.1 | very good quality |
| [P1](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part1of6) [P2](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part2of6) [P3](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part3of6) [P4](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part4of6) [P5](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part5of6) [P6](https://huggingface.co/mradermacher/Qwen3-235B-A22B-Thinking-2507-GGUF/resolve/main/Qwen3-235B-A22B-Thinking-2507.Q8_0.gguf.part6of6) | Q8_0 | 250.0 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
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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