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jina-embeddings-v5-text-nano-retrieval-GGUF

Name: jina-embeddings-v5-text-nano-retrieval-GGUF
Author: jinaai

by jinaai · source Hugging Face · updated 2026-02-27

cc-by-nc-4.0150 MB~1 GB RAMsource aliveunlabeled

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Source and license

Source: https://huggingface.co/jinaai/jina-embeddings-v5-text-nano-retrieval-GGUF
License: cc-by-nc-4.0 (restricted license: terms at the source apply)
Requirements: about 1 GB of RAM, 150 MB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp.
Tags: llama.cpp gguf embedding eurobert llama-cpp jina-embeddings-v5 sentence-similarity multilingual feature-extraction

Numbers

4,575 downloads on Hugging Face
4 likes
license cc-by-nc-4.0
0.1 GB for v5-nano-retrieval-Q4_K_M.gguf
327,838 npm downloads a week for node-llama-cpp
latest node-llama-cpp@3.22.1

Numbers as of 2026-10-02 21:00 UTC, from the source API.

Summary

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Files

file	quant	size
`v5-nano-retrieval-F16.gguf`	F16	411 MB
`v5-nano-retrieval-IQ1_M.gguf`	IQ1_M	97 MB
`v5-nano-retrieval-IQ1_S.gguf`	IQ1_S	95 MB
`v5-nano-retrieval-IQ2_M.gguf`	IQ2_M	108 MB
`v5-nano-retrieval-IQ2_XXS.gguf`	IQ2_XXS	101 MB
`v5-nano-retrieval-IQ4_NL.gguf`	IQ4_NL	145 MB
`v5-nano-retrieval-IQ4_XS.gguf`	IQ4_XS	142 MB
`v5-nano-retrieval-Q2_K.gguf`	Q2_K	124 MB
`v5-nano-retrieval-Q3_K_M.gguf`	Q3_K_M	137 MB
`v5-nano-retrieval-Q4_K_M.gguf`	Q4_K_M	150 MB
`v5-nano-retrieval-Q5_K_M.gguf`	Q5_K_M	161 MB
`v5-nano-retrieval-Q5_K_S.gguf`	Q5_K_S	159 MB
`v5-nano-retrieval-Q6_K.gguf`	Q6_K	173 MB
`v5-nano-retrieval-Q8_0.gguf`	Q8_0	222 MB

From the source README

jina-embeddings-v5-text-nano-retrieval-GGUF

GGUF quantizations of jina-embeddings-v5-text-nano-retrieval using llama.cpp. A 239M parameter multilingual embedding model quantized for efficient inference.

Elastic Inference Service | ArXiv | Blog

> [!IMPORTANT]
> We highly recommend to first read this blog post for more technical details and customized llama.cpp build.

Overview

`jina-embeddings-v5-text-nano-retrieval` is a task-specific embedding model for retrieval, part of the jina-embeddings-v5-text model family.
| Feature | Value |
| --- | --- |
| Parameters | 239M |
| Task | `retrieval` |
| Embedding Dimension | 768 |
| Matryoshka Dimensions | 32, 64, 128, 256, 512, 768 |
| Pooling Strategy | Last-token pooling |
| Base Model | jina-embeddings-v5-text-nano |

Usage with llama.cpp

via Elastic Inference Service

The fastest way to use v5-text in production. Elastic Inference Service (EIS) provides managed embedding inference with built-in scaling, so you can generate embeddings directly within your Elastic deployment.

PUT _inference/text_embedding/jina-v5
{
  "service": "elastic",
  "service_settings": {
    "model_id": "jina-embeddings-v5-text-nano"
  }
}

See the Elastic Inference Service documentation for setup details.

# Build llama.cpp (upstream)
git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp…

Card id model:hf:jinaai/jina-embeddings-v5-text-nano-retrieval-GGUF · collected 2026-10-02 21:00 UTC · JSON