{"v":1,"id":"model:hf:ChristianAzinn/mxbai-embed-large-v1-gguf","slug":"model-christianazinn-mxbai-embed-large-v1-gguf","kind":"model","category":"embedding","title":"mxbai-embed-large-v1-gguf","summary":"This is our base sentence embedding model. It was trained using AnglE loss on our high-quality large scale data. It achieves SOTA performance on BERT-large scale. Find out more in our blog post.","source":{"provider":"hf","ref":"ChristianAzinn/mxbai-embed-large-v1-gguf","url":"https://huggingface.co/ChristianAzinn/mxbai-embed-large-v1-gguf","rev":"3ec6d46af11ba2b982d8c6a1e11183c4995f76a7","fetchedAt":"2026-10-02T21:01:23.411Z","etag":"W/\"13c9-sYe/+I+Nz+ygAs6uK4TAmjB+jX0\""},"author":{"name":"ChristianAzinn","url":"https://huggingface.co/ChristianAzinn"},"license":{"spdx":"apache-2.0","raw":"apache-2.0","open":true},"metrics":{"downloads":238659,"downloadsWeek":4402710,"likes":8,"takenAt":"2026-10-02T21:01:23.411Z"},"tags":["sentence-transformers","gguf","mteb","transformers","transformers.js","feature-extraction","en","deploy:azure"],"pipeline":"feature-extraction","links":{"github":"mixedbread-ai/batched","npm":"@huggingface/transformers"},"updatedAt":"2024-04-07T21:56:31.000Z","collectedAt":"2026-10-02T21:01:23.411Z","review":{"numbers":["238,659 downloads on Hugging Face","8 likes","license apache-2.0","0.2 GB for mxbai-embed-large-v1.Q4_K_M.gguf","4,402,710 npm downloads a week for @huggingface/transformers","latest @huggingface/transformers@4.3.0"],"log":null},"trust":"unlabeled","health":{"status":"alive","checkedAt":"2026-10-02T21:01:23.411Z","http":200},"description":"# mxbai-embed-large-v1-gguf\n\nModel creator: [MixedBread AI](https://huggingface.co/mixedbread-ai)\n\nOriginal model: [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1)\n\n## Original Description\n\nThis is our base sentence embedding model. It was trained using [AnglE](https://arxiv.org/abs/2309.12871) loss on our high-quality large scale data. It achieves SOTA performance on BERT-large scale. Find out more in our [blog post](https://mixedbread.ai/blog/mxbai-embed-large-v1).\n\n## Description\n\nThis repo contains GGUF format files for the [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) embedding model.\n\nThese files were converted and quantized with llama.cpp [PR 5500](https://github.com/ggerganov/llama.cpp/pull/5500), commit [34aa045de](https://github.com/ggerganov/llama.cpp/pull/5500/commits/34aa045de44271ff7ad42858c75739303b8dc6eb), on a consumer RTX 4090.\n\nThis model supports up to 512 tokens of context.\n\n## Compatibility\n\nThese files are compatible with [llama.cpp](https://github.com/ggerganov/llama.cpp) as of commit [4524290e8](https://github.com/ggerganov/llama.cpp/commit/4524290e87b8e107cc2b56e1251751546f4b9051), as well as [LM Studio](https://lmstudio.ai/) as of version 0.2.19.\n\n# Meta-information\n## Explanation of quantisation methods\n\n  Click to see details\nThe methods available are:\n* GGML_TYPE_Q2_K - \"type-1\" 2-bit quantization in super-blocks containing 16 blocks, each block having 16 weight. Block scales and mins are quantized with 4 bits. This ends up effectively using 2.5625 bits per weight (bpw)\n* GGML_TYPE_Q3_K - \"type-0\" 3-bit quantization in super-blocks containing 16 blocks, each block having 16 weights. Scales are quantized with 6 bits. This end up using 3.4375 bpw.\n* GGML_TYPE_Q4_K - \"type-1\" 4-bit quantization in super-blocks containing 8 blocks, each block having 32 weights. Scales and mins are quantized with 6 bi…\n\nSource: https://huggingface.co/ChristianAzinn/mxbai-embed-large-v1-gguf","install":{"kind":"model","hfId":"ChristianAzinn/mxbai-embed-large-v1-gguf","gated":false,"format":"gguf","files":[{"name":"mxbai-embed-large-v1.Q2_K.gguf","size":144227872,"quant":"Q2_K","sha256":"d7fe8249e4f854c333ea0b725ce022fe69dc7d1f95692e9747cc26d8c6f49263"},{"name":"mxbai-embed-large-v1.Q3_K_L.gguf","size":198491680,"quant":"Q3_K_L","sha256":"6a6ddb4acd4e75365ae4e32ed82d0d35dc6b217b4c66638e73990ffcd02b3605"},{"name":"mxbai-embed-large-v1.Q3_K_M.gguf","size":181452320,"quant":"Q3_K_M","sha256":"a6ed5b012d07ccb492d102ede8a4f85b882822b6e0add7cfc9d1ef7f6632217c"},{"name":"mxbai-embed-large-v1.Q3_K_S.gguf","size":159563296,"quant":"Q3_K_S","sha256":"3e075541980e2f83c8db80f032e4c8797f443da9ffad3c944f3086d027a2139c"},{"name":"mxbai-embed-large-v1.Q4_0.gguf","size":199671328,"quant":"Q4_0","sha256":"6ba855bf271195b32c99678429e6216ac129378f4e0eae8afc6279a3a376588e"},{"name":"mxbai-embed-large-v1.Q4_K_M.gguf","size":215891488,"quant":"Q4_K_M","sha256":"3869d462819e3f6cd2c1b0f8d6817e95cc1ed31fc09388432669209d1c6f1b65"},{"name":"mxbai-embed-large-v1.Q4_K_S.gguf","size":203341344,"quant":"Q4_K_S","sha256":"8cb468ef537172fb70324dfd0d77ff551852f483f175b3b49ea7fcfa70417833"},{"name":"mxbai-embed-large-v1.Q5_0.gguf","size":237420064,"quant":"Q5_0","sha256":"fa8567f95c8f3f5df94b5921d5a10e7eb4b9974cc16e62d3862f681e67212e30"},{"name":"mxbai-embed-large-v1.Q5_K_M.gguf","size":245775904,"quant":"Q5_K_M","sha256":"747376b7479f0f31ce5f6147052010858eeee5aa9d3637fdfed1ab1a9c013eba"},{"name":"mxbai-embed-large-v1.Q5_K_S.gguf","size":237420064,"quant":"Q5_K_S","sha256":"79463a58bfdb6bc3acb28530383ec1f2c6778ea0e895c12238593fe4db23488a"},{"name":"mxbai-embed-large-v1.Q6_K.gguf","size":277528096,"quant":"Q6_K","sha256":"4c439ed175c6de17be56aa797c5c8503c1f9ea2da6a5d528d968c95c7b391577"},{"name":"mxbai-embed-large-v1.Q8_0.gguf","size":358235712,"quant":"Q8_0","sha256":"bcdebca12aa16c0e51d166d97e4776efd46f905952b0c9acb968976eba2619f3"},{"name":"mxbai-embed-large-v1_fp16.gguf","size":669603712,"sha256":"819c2adf5ce6df2b6bd2ae4ca90d2a69f060afeb438d0c171db57daa02e39c3d"},{"name":"mxbai-embed-large-v1_fp32.gguf","size":1337141120,"sha256":"bd5c23282f72b801a87964813972aca16fbb13ddca9d540b99f7934475da27dc"}],"totalBytes":4665764000,"suggestedFile":"mxbai-embed-large-v1.Q4_K_M.gguf","requirements":{"ramGb":1,"diskBytes":215891488,"note":"estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models"},"runWith":["llama.cpp"],"command":"lsh models install hf:ChristianAzinn/mxbai-embed-large-v1-gguf"}}