--- base_model: deepseek-ai/DeepSeek-V2.5-1210 language: - en library_name: transformers license: other license_link: https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-MODEL license_name: deepseek quantized_by: mradermacher --- ## About static quants of https://huggingface.co/deepseek-ai/DeepSeek-V2.5-1210 weighted/imatrix quants are available at https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-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/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q2_K.gguf.part2of2) | Q2_K | 86.0 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_S.gguf.part3of3) | Q3_K_S | 101.8 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_M.gguf.part3of3) | Q3_K_M | 112.8 | lower quality | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_L.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_L.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q3_K_L.gguf.part3of3) | Q3_K_L | 122.5 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.IQ4_XS.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.IQ4_XS.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.IQ4_XS.gguf.part3of3) | IQ4_XS | 126.9 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_S.gguf.part3of3) | Q4_K_S | 134.0 | fast, recommended | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q4_K_M.gguf.part3of3) | Q4_K_M | 142.6 | fast, recommended | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_S.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_S.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_S.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_S.gguf.part4of4) | Q5_K_S | 162.4 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_M.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_M.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_M.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q5_K_M.gguf.part4of4) | Q5_K_M | 167.3 | | | [PART 1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q6_K.gguf.part1of4) [PART 2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q6_K.gguf.part2of4) [PART 3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q6_K.gguf.part3of4) [PART 4](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q6_K.gguf.part4of4) | Q6_K | 193.6 | very good quality | | [P1](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part1of6) [P2](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part2of6) [P3](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part3of6) [P4](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part4of6) [P5](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part5of6) [P6](https://huggingface.co/mradermacher/DeepSeek-V2.5-1210-GGUF/resolve/main/DeepSeek-V2.5-1210.Q8_0.gguf.part6of6) | Q8_0 | 250.7 | 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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.