{"v":1,"id":"model:hf:nomic-ai/nomic-embed-text-v1.5-GGUF","slug":"model-nomic-ai-nomic-embed-text-v1-5-gguf","kind":"model","category":"embedding","title":"nomic-embed-text-v1.5-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-v1.5-GGUF","url":"https://huggingface.co/nomic-ai/nomic-embed-text-v1.5-GGUF","rev":"0188c9bf409793f810680a5a431e7b899c46104c","fetchedAt":"2026-10-02T21:01:17.407Z","etag":"W/\"135a-pb9xXeHVi60o4ZHRKBMqYcf4Kto\""},"author":{"name":"nomic-ai","url":"https://huggingface.co/nomic-ai"},"license":{"spdx":"apache-2.0","raw":"apache-2.0","open":true},"metrics":{"downloads":313050,"downloadsWeek":4402710,"likes":137,"takenAt":"2026-10-02T21:01:17.407Z"},"tags":["gguf","feature-extraction","sentence-similarity","en"],"pipeline":"sentence-similarity","links":{"github":"nomic-ai/nomic","npm":"@huggingface/transformers"},"updatedAt":"2025-04-28T20:14:53.000Z","collectedAt":"2026-10-02T21:01:17.407Z","review":{"numbers":["313,050 downloads on Hugging Face","137 likes","license apache-2.0","0.1 GB for nomic-embed-text-v1.5.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":"2026-10-02T21:01:17.407Z","http":200},"description":"# nomic-embed-text-v1.5 - GGUF\n\nOriginal model: [nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)\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-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5).\n\n## Description\n\nThis repo contains llama.cpp-compatible files for [nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5) 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-v1.5.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-v1.5.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…\n\nSource: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5-GGUF","install":{"kind":"model","hfId":"nomic-ai/nomic-embed-text-v1.5-GGUF","gated":false,"format":"gguf","files":[{"name":"nomic-embed-text-v1.5.Q2_K.gguf","size":49361088,"quant":"Q2_K","sha256":"a25579241bc4d68d246fe9e12720dda4ed2f735d18e677a207d01d55591f6907"},{"name":"nomic-embed-text-v1.5.Q3_K_L.gguf","size":71593088,"quant":"Q3_K_L","sha256":"8a1a7423f3634491a1dbd25b1c1934e90aa721ab409e5871fc82e9914d304f21"},{"name":"nomic-embed-text-v1.5.Q3_K_M.gguf","size":67169408,"quant":"Q3_K_M","sha256":"dd69e0ee67706a0dba210e5cf9051b55615231d6c6197a8b99e717bdd19586a4"},{"name":"nomic-embed-text-v1.5.Q3_K_S.gguf","size":59649152,"quant":"Q3_K_S","sha256":"5818855f9ca49f00b2b20e2d0dd32d6c7443ec10e2ee7ad657c85b94c473699c"},{"name":"nomic-embed-text-v1.5.Q4_0.gguf","size":77802880,"quant":"Q4_0","sha256":"8d88b9d579f2dcce28f65de1ad3946453adc281d7b784f2a75afe25158136d44"},{"name":"nomic-embed-text-v1.5.Q4_K_M.gguf","size":84106624,"quant":"Q4_K_M","sha256":"d4e388894e09cf3816e8b0896d81d265b55e7a9fff9ab03fe8bf4ef5e11295ac"},{"name":"nomic-embed-text-v1.5.Q4_K_S.gguf","size":78097792,"quant":"Q4_K_S","sha256":"82c99fedbec31354a2d880c9741be151aef4a20a5712b67f4ee2b088d197b77e"},{"name":"nomic-embed-text-v1.5.Q5_0.gguf","size":94888768,"quant":"Q5_0","sha256":"d1fc6492a18f92e0662c9704f3cb457458e04f5193a1adf1f5a7304be6468559"},{"name":"nomic-embed-text-v1.5.Q5_K_M.gguf","size":99588928,"quant":"Q5_K_M","sha256":"0c7930f6c4f6f29b7da5046e3a2c0832aa3f602db3de5760a95f0582dbd3d6e6"},{"name":"nomic-embed-text-v1.5.Q5_K_S.gguf","size":94888768,"quant":"Q5_K_S","sha256":"07782a46f2d36931b7ca28e4b4f1d88aea1fb3e1704a7e5fc6a8be104195bd51"},{"name":"nomic-embed-text-v1.5.Q6_K.gguf","size":113042528,"quant":"Q6_K","sha256":"9b335d0801aded377a055257f7cf046daa48dd0bc2a7c2ea3300168c154b1fd9"},{"name":"nomic-embed-text-v1.5.Q8_0.gguf","size":146146432,"quant":"Q8_0","sha256":"3e24342164b3d94991ba9692fdc0dd08e3fd7362e0aacc396a9a5c54a544c3b7"},{"name":"nomic-embed-text-v1.5.f16.gguf","size":274290560,"quant":"F16","sha256":"f7af6f66802f4df86eda10fe9bbcfc75c39562bed48ef6ace719a251cf1c2fdb"},{"name":"nomic-embed-text-v1.5.f32.gguf","size":547664768,"quant":"F32","sha256":"ed3a84b570c5513bfd6bfe0ed4cdc8d5a5de5c6b5029fbbc2822d59fc893c1f8"}],"totalBytes":1858290784,"suggestedFile":"nomic-embed-text-v1.5.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-v1.5-GGUF"}}