🧠
Jina Embeddings V3 model by jinaai
⭐ 49.7
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Model

Jina Embeddings V3

by jinaai jinaai/jina-embeddings-v3
Free2AITools Nexus Index
49.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 58
P: Popularity 74
R: Recency 87
Q: Quality 65
Tech Context
0.57B Params
4.096K Ctx
Vital Performance
5.3M DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 49.7 FNI Score
Tiny 0.57B Params
4k Context
Hot 5.3M Downloads
8G GPU ~2GB Est. VRAM
Dense XLMROBERTAMODEL Architecture
Restricted CC License
Model Information Summary
Entity Passport
Registry ID jinaai/jina-embeddings-v3
License CC-BY-NC-4.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{jinaai_jina_embeddings_v3,
  author = {jinaai},
  title = {Jina Embeddings V3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/jinaai/jina-embeddings-v3}},
  note = {Accessed via Free2AITools.}
}
APA Style
jinaai. (2026). Jina Embeddings V3 [Model]. Free2AITools. https://huggingface.co/jinaai/jina-embeddings-v3

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run jina-embeddings-v3
πŸ€— HF Download
huggingface-cli download jinaai/jina-embeddings-v3
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 58
Popularity (P) 74
Recency (R) 87
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Jina Embeddings V3: Authority (A:58), Popularity (P:74), Recency (R:87), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
5.3MDownloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--jinaai--jina-embeddings-v3
slug
jinaai--jina-embeddings-v3
source
huggingface
author
jinaai
license
CC-BY-NC-4.0
tags
transformers, pytorch, onnx, safetensors, feature-extraction, sentence-similarity, mteb, sentence-transformers, custom_code, multilingual, af, am, ar, as, az, be, bg, bn, br, bs, ca, cs, cy, da, de, el, en, eo, es, et, eu, fa, fi, fr, fy, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, is, it, ja, jv, ka, kk, km, kn, ko, ku, ky, la, lo, lt, lv, mg, mk, ml, mn, mr, ms, my, ne, nl, no, om, or, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, so, sq, sr, su, sv, sw, ta, te, th, tl, tr, ug, uk, ur, uz, vi, x

βš™οΈ Technical Specs

architecture
XLMRobertaModel
params billions
0.57
context length
4,096
pipeline tag
feature-extraction
vram gb
1.7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
5,309,013
stars
0
forks
0

Data indexed from public sources. Updated daily.