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--- |
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base_model: swiss-ai/Apertus-8B-Instruct-2509 |
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extra_gated_button_content: Submit |
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Affiliation: text |
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By clicking Submit below I accept the terms of use: checkbox |
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Your Name: text |
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geo: ip_location |
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extra_gated_prompt: "### Apertus LLM Acceptable Use Policy \n(1.0 | September 1, |
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2025)\n\"Agreement\" The Swiss National AI Institute (SNAI) is a partnership between |
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the two Swiss Federal Institutes of Technology, ETH Zurich and EPFL. \n\nBy using |
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the Apertus LLM you agree to indemnify, defend, and hold harmless ETH Zurich and |
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EPFL against any third-party claims arising from your use of Apertus LLM. \n\nThe |
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training data and the Apertus LLM may contain or generate information that directly |
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or indirectly refers to an identifiable individual (Personal Data). You process |
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Personal Data as independent controller in accordance with applicable data protection |
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law. SNAI will regularly provide a file with hash values for download which you |
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can apply as an output filter to your use of our Apertus LLM. The file reflects |
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data protection deletion requests which have been addressed to SNAI as the developer |
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of the Apertus LLM. It allows you to remove Personal Data contained in the model |
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output. We strongly advise downloading and applying this output filter from SNAI |
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every six months following the release of the model. " |
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language: |
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- en |
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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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- multilingual |
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- compliant |
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- swiss-ai |
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- apertus |
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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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<!-- ### vocab_type: --> |
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<!-- ### tags: --> |
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<!-- ### 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 --> |
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<!-- ### quants_skip: --> |
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<!-- ### skip_mmproj: --> |
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static quants of https://huggingface.co/swiss-ai/Apertus-8B-Instruct-2509 |
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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#Apertus-8B-Instruct-2509-GGUF).*** |
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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. |
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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/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q2_K.gguf) | Q2_K | 3.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q3_K_S.gguf) | Q3_K_S | 3.8 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q3_K_M.gguf) | Q3_K_M | 4.3 | lower quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q3_K_L.gguf) | Q3_K_L | 4.7 | | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q4_K_M.gguf) | Q4_K_M | 5.2 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q6_K.gguf) | Q6_K | 6.7 | very good quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.Q8_0.gguf) | Q8_0 | 8.7 | fast, best quality | |
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| [GGUF](https://huggingface.co/mradermacher/Apertus-8B-Instruct-2509-GGUF/resolve/main/Apertus-8B-Instruct-2509.f16.gguf) | f16 | 16.2 | 16 bpw, overkill | |
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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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