mradermacher/ministral-3-14b-reasoning-2512-plumesper1.1-gguf overview

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      "sequelbox/Tachibana3-Part2-DeepSeek-V3.2"
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    "frontmatter": {
      "base_model": "sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1",
      "datasets": [
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        "sequelbox/Titanium3-DeepSeek-V3.1-Terminus",
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        "sequelbox/Tachibana3-Part2-DeepSeek-V3.2"
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      "language": [
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        "engineer",
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    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1\ndatasets:\n- sequelbox/Celestia3-DeepSeek-R1-0528\n- sequelbox/Mitakihara-DeepSeek-R1-0528\n- sequelbox/Raiden-DeepSeek-R1\n- sequelbox/Titanium3-DeepSeek-V3.1-Terminus\n- sequelbox/Tachibana3-Part1-DeepSeek-V3.1-Terminus\n- sequelbox/Tachibana3-Part2-DeepSeek-V3.2\nlanguage:\n- en\nlibrary_name: transformers\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- mergekit\n- merge\n- esper\n- shining-valiant\n- valiant\n- mistral3\n- mistral\n- mistral-common\n- ministral-3-14b\n- ministral\n- reasoning\n- code\n- code-reasoning\n- code-instruct\n- python\n- javascript\n- dev-ops\n- jenkins\n- terraform\n- scripting\n- powershell\n- azure\n- aws\n- gcp\n- cloud\n- science\n- science-reasoning\n- physics\n- biology\n- chemistry\n- earth-science\n- astronomy\n- machine-learning\n- artificial-intelligence\n- compsci\n- computer-science\n- information-theory\n- ML-Ops\n- math\n- cuda\n- deep-learning\n- transformers\n- agentic\n- LLM\n- neuromorphic\n- self-improvement\n- complex-systems\n- cognition\n- linguistics\n- philosophy\n- logic\n- epistemology\n- simulation\n- game-theory\n- knowledge-management\n- creativity\n- problem-solving\n- architect\n- engineer\n- developer\n- creative\n- analytical\n- expert\n- rationality\n- conversational\n- chat\n- instruct\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\n<!-- ### 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 -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/sequelbox/Ministral-3-14B-Reasoning-2512-PlumEsper1.1\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-i1-GGUF\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.6 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.mmproj-f16.gguf) | mmproj-f16 | 1.0 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q2_K.gguf) | Q2_K | 5.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q3_K_S.gguf) | Q3_K_S | 6.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q3_K_M.gguf) | Q3_K_M | 6.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q3_K_L.gguf) | Q3_K_L | 7.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.IQ4_XS.gguf) | IQ4_XS | 7.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q4_K_S.gguf) | Q4_K_S | 7.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q4_K_M.gguf) | Q4_K_M | 8.3 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q5_K_S.gguf) | Q5_K_S | 9.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q5_K_M.gguf) | Q5_K_M | 9.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q6_K.gguf) | Q6_K | 11.2 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Ministral-3-14B-Reasoning-2512-PlumEsper1.1-GGUF/resolve/main/Ministral-3-14B-Reasoning-2512-PlumEsper1.1.Q8_0.gguf) | Q8_0 | 14.5 | fast, best quality |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
    "related_quantizations": []
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