🧠
Jina Embeddings V4 Vllm Retrieval model by jinaai
⭐ 41.9
🧠
Model

Jina Embeddings V4 Vllm Retrieval

by jinaai hf-model--jinaai--jina-embeddings-v4-vllm-retrieval
Nexus Index
41.9 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 54
R: Recency 64
Q: Quality 65
Tech Context
Vital Performance
52.6K DL / 30D
0.0%
Source →
Audited 41.9 FNI Score
Tiny - Params
- Context
Hot 52.6K Downloads
Model Information Summary
Entity Passport
Registry ID hf-model--jinaai--jina-embeddings-v4-vllm-retrieval
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__jinaai__jina_embeddings_v4_vllm_retrieval,
  author = {jinaai},
  title = {Jina Embeddings V4 Vllm Retrieval Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/jinaai/jina-embeddings-v4-vllm-retrieval}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
jinaai. (2026). Jina Embeddings V4 Vllm Retrieval [Model]. Free2AITools. https://huggingface.co/jinaai/jina-embeddings-v4-vllm-retrieval

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download jinaai/jina-embeddings-v4-vllm-retrieval
📦 Install Lib
pip install -U transformers

⚖️ Nexus Index V2.0

Methodology Index Protocol
41.9
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 54
Recency (R) 64
Quality (Q) 65

💬 Index Insight

FNI V2.0 for Jina Embeddings V4 Vllm Retrieval: Semantic (S:50), Authority (A:0), Popularity (P:54), Recency (R:64), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

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Deployment Guide

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Technical Deep Dive

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

⚠️ 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 →

📝 Limitations & Considerations

  • • Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • • VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • • 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
52.6KDownloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--jinaai--jina-embeddings-v4-vllm-retrieval
slug
jinaai--jina-embeddings-v4-vllm-retrieval
source
huggingface
author
jinaai
license
tags
transformers, safetensors, qwen2_5_vl, image-text-to-text, vidore, colpali, multimodal-embedding, multilingual-embedding, text-to-visual document (t→vd) retrieval, feature-extraction, sentence-similarity, mteb, visual-document-retrieval, multilingual, arxiv:2506.18902, text-generation-inference, endpoints_compatible, region:eu

⚙️ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
visual-document-retrieval

📊 Engagement & Metrics

downloads
52,599
stars
0
forks
0

Data indexed from public sources. Updated daily.