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nomic-embed-text-v1-GGUF
by nomic-ai · source Hugging Face · updated 2025-04-28
apache-2.080 MB~1 GB RAMsource aliveunlabeled
Embedding text with nomic-embed-text requires task instruction prefixes at the beginning of each string.
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Source and license
- Source: https://huggingface.co/nomic-ai/nomic-embed-text-v1-GGUF
- License: apache-2.0
- Requirements: about 1 GB of RAM, 80 MB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp.
- Tags:
gguffeature-extractionsentence-similarityen
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
Numbers as of 2026-10-02 20:53 UTC, from the source API.
Summary
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Files
| file | quant | size |
|---|---|---|
nomic-embed-text-v1.Q2_K.gguf | Q2_K | 47 MB |
nomic-embed-text-v1.Q3_K_L.gguf | Q3_K_L | 68 MB |
nomic-embed-text-v1.Q3_K_M.gguf | Q3_K_M | 64 MB |
nomic-embed-text-v1.Q3_K_S.gguf | Q3_K_S | 57 MB |
nomic-embed-text-v1.Q4_0.gguf | Q4_0 | 74 MB |
nomic-embed-text-v1.Q4_K_M.gguf | Q4_K_M | 80 MB |
nomic-embed-text-v1.Q4_K_S.gguf | Q4_K_S | 74 MB |
nomic-embed-text-v1.Q5_0.gguf | Q5_0 | 90 MB |
nomic-embed-text-v1.Q5_K_M.gguf | Q5_K_M | 95 MB |
nomic-embed-text-v1.Q5_K_S.gguf | Q5_K_S | 90 MB |
nomic-embed-text-v1.Q6_K.gguf | Q6_K | 108 MB |
nomic-embed-text-v1.Q8_0.gguf | Q8_0 | 139 MB |
nomic-embed-text-v1.f16.gguf | F16 | 262 MB |
nomic-embed-text-v1.f32.gguf | F32 | 522 MB |
From the source README
nomic-embed-text-v1 - GGUF
Original model: nomic-embed-text-v1
Usage
Embedding text with `nomic-embed-text` requires task instruction prefixes at the beginning of each string.
For example, the code below shows how to use the `search_query` prefix to embed user questions, e.g. in a RAG application.
To see the full set of task instructions available & how they are designed to be used, visit the model card for nomic-embed-text-v1.
Description
This repo contains llama.cpp-compatible files for nomic-embed-text-v1 in GGUF format.
llama.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.
Example `llama.cpp` Command
Compute a single embedding:
```shell
./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?'
```
You 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.
Card id model:hf:nomic-ai/nomic-embed-text-v1-GGUF · collected 2026-10-02 20:53 UTC · JSON