--- base_model: temaq-org/Tema_Q-X5-Thinking language: - ja - en - zh library_name: transformers mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - qwen - qwen3.6 - transformer - instruction-tuned - multilingual - uncensored - non-censored - unfiltered --- ## About static quants of https://huggingface.co/temaq-org/Tema_Q-X5-Thinking ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Tema_Q-X5-Thinking-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-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/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.1 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.mmproj-f16.gguf) | mmproj-f16 | 0.1 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q2_K.gguf) | Q2_K | 13.0 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q3_K_S.gguf) | Q3_K_S | 15.3 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q3_K_M.gguf) | Q3_K_M | 16.9 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q3_K_L.gguf) | Q3_K_L | 18.2 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.IQ4_XS.gguf) | IQ4_XS | 19.0 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q4_K_S.gguf) | Q4_K_S | 20.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q4_K_M.gguf) | Q4_K_M | 21.3 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q5_K_S.gguf) | Q5_K_S | 24.1 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q5_K_M.gguf) | Q5_K_M | 24.8 | | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q6_K.gguf) | Q6_K | 28.6 | very good quality | | [GGUF](https://huggingface.co/mradermacher/Tema_Q-X5-Thinking-GGUF/resolve/main/Tema_Q-X5-Thinking.Q8_0.gguf) | Q8_0 | 37.0 | 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.
