{"v":1,"id":"model:hf:nomic-ai/nomic-embed-text-v1-GGUF","slug":"model-nomic-ai-nomic-embed-text-v1-gguf","kind":"model","category":"embedding","title":"nomic-embed-text-v1-GGUF","summary":"Embedding text with nomic-embed-text requires task instruction prefixes at the beginning of each string.","source":{"provider":"hf","ref":"nomic-ai/nomic-embed-text-v1-GGUF","url":"https://huggingface.co/nomic-ai/nomic-embed-text-v1-GGUF","rev":"90c80ac5c2a0d13de9a36cf1dec39f34acee54a8","fetchedAt":"2026-10-02T20:53:45.080Z","etag":"W/\"12a5-b8JiQYp59Yr8dj8xo3pxVE3gR3A\""},"author":{"name":"nomic-ai","url":"https://huggingface.co/nomic-ai"},"license":{"spdx":"apache-2.0","raw":"apache-2.0","open":true},"metrics":{"downloads":9142,"downloadsWeek":4402710,"likes":7,"takenAt":"2026-10-02T20:53:45.080Z"},"tags":["gguf","feature-extraction","sentence-similarity","en"],"pipeline":"sentence-similarity","links":{"github":"nomic-ai/nomic","npm":"@huggingface/transformers"},"updatedAt":"2025-04-28T20:27:02.000Z","collectedAt":"2026-10-02T20:53:45.080Z","review":{"numbers":["9,142 downloads on Hugging Face","7 likes","license apache-2.0","0.1 GB for nomic-embed-text-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":"2026-10-02T20:53:45.080Z","http":200},"description":"# nomic-embed-text-v1 - GGUF\n\nOriginal model: [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1)\n\n## Usage\n\nEmbedding text with `nomic-embed-text` requires task instruction prefixes at the beginning of each string.\n\nFor example, the code below shows how to use the `search_query` prefix to embed user questions, e.g. in a RAG application.\n\nTo see the full set of task instructions available & how they are designed to be used, visit the model card for [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1).\n\n## Description\n\nThis repo contains llama.cpp-compatible files for [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1) in GGUF format.\n\nllama.cpp will default to 2048 tokens of context with these files. For the full 8192 token context length, you will have to choose a context extension method. The 🤗 Transformers model uses Dynamic NTK-Aware RoPE scaling, but that is not currently available in llama.cpp.\n\n## Example `llama.cpp` Command\n\nCompute a single embedding:\n```shell\n./embedding -ngl 99 -m nomic-embed-text-v1.f16.gguf -c 8192 -b 8192 --rope-scaling yarn --rope-freq-scale .75 -p 'search_query: What is TSNE?'\n```\n\nYou can also submit a batch of texts to embed, as long as the total number of tokens does not exceed the context length. Only the first three embeddings are shown by the `embedding` example.\n\ntexts.txt:\n```\nsearch_query: What is TSNE?\nsearch_query: Who is Laurens Van der Maaten?\n```\n\nCompute multiple embeddings:\n```shell\n./embedding -ngl 99 -m nomic-embed-text-v1.f16.gguf -c 8192 -b 8192 --rope-scaling yarn --rope-freq-scale .75 -f texts.txt\n```\n\n## Compatibility\n\nThese files are compatible with llama.cpp as of commit [4524290e8](https://github.com/ggerganov/llama.cpp/commit/4524290e87b8e107cc2b56e1251751546f4b9051) from 2/15/2024.\n\n## Provided Files\n\nThe below table shows the mean squared error of the embeddings produced…\n\nSource: https://huggingface.co/nomic-ai/nomic-embed-text-v1-GGUF","install":{"kind":"model","hfId":"nomic-ai/nomic-embed-text-v1-GGUF","gated":false,"format":"gguf","files":[{"name":"nomic-embed-text-v1.Q2_K.gguf","size":49361088,"quant":"Q2_K","sha256":"afb87e81c67d34db721db27f093d1e87e4620001fe11e4566c5ceb88cd0fc667"},{"name":"nomic-embed-text-v1.Q3_K_L.gguf","size":71593088,"quant":"Q3_K_L","sha256":"a1974d4dd71b76ae3a44b58c12bd753fd57f08975a81a77960097e285a01eb32"},{"name":"nomic-embed-text-v1.Q3_K_M.gguf","size":67169408,"quant":"Q3_K_M","sha256":"6b5811832d7bf8cae9ec2824128e25a7b69bc752a7c993893df7ec80ff506424"},{"name":"nomic-embed-text-v1.Q3_K_S.gguf","size":59649152,"quant":"Q3_K_S","sha256":"60c6e5a619c66d210da3058e4a36aeab1c49386fa4836cb165f2e81182875fde"},{"name":"nomic-embed-text-v1.Q4_0.gguf","size":77802880,"quant":"Q4_0","sha256":"ca39592bb0191be78b0fa9263b96792203eaad7bd9de0d53ad7f07c1f7d59dc5"},{"name":"nomic-embed-text-v1.Q4_K_M.gguf","size":84106624,"quant":"Q4_K_M","sha256":"7b910918b82f87301b0301134c4a131a15a6123962e8b89a0554ba7357d285fb"},{"name":"nomic-embed-text-v1.Q4_K_S.gguf","size":78097792,"quant":"Q4_K_S","sha256":"9b72dd549a1589e4047ed3cd737ba6ae974ae635a0e327f4352c56536573b9d4"},{"name":"nomic-embed-text-v1.Q5_0.gguf","size":94888768,"quant":"Q5_0","sha256":"c3fac9da3c08434befcd3f4353e68df0f2b61dc200ee7b8a38afccf55e7fb0e7"},{"name":"nomic-embed-text-v1.Q5_K_M.gguf","size":99588928,"quant":"Q5_K_M","sha256":"9b27adf775cc6976755da192c1982877c54c2cbbd2f47552b4189d96829657d0"},{"name":"nomic-embed-text-v1.Q5_K_S.gguf","size":94888768,"quant":"Q5_K_S","sha256":"6e1590be631a94d824c148b2f1d4297c94edf35f538c17554ccc75ee44c377e5"},{"name":"nomic-embed-text-v1.Q6_K.gguf","size":113042528,"quant":"Q6_K","sha256":"c80b0668ea5ce20f55075cd46237944172b93f61907b47fa022fe35eaf05181d"},{"name":"nomic-embed-text-v1.Q8_0.gguf","size":146146432,"quant":"Q8_0","sha256":"194206fcf0e77681bd2eaa3517b6fce880e1a3e15ef89935a77a1892574d15f7"},{"name":"nomic-embed-text-v1.f16.gguf","size":274290560,"quant":"F16","sha256":"e17ebde8d22d345aead60b0ed10726e8c45a06f4ba9a45223ab594526542e58f"},{"name":"nomic-embed-text-v1.f32.gguf","size":547664768,"quant":"F32","sha256":"1798c9e108b1d27fe3501339ac7785ea37f6504ee928ef7802ad881219e4c04c"}],"totalBytes":1858290784,"suggestedFile":"nomic-embed-text-v1.Q4_K_M.gguf","requirements":{"ramGb":1,"diskBytes":84106624,"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:nomic-ai/nomic-embed-text-v1-GGUF"}}