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Jina Embeddings V4 Vllm Retrieval model by jinaai
⭐ 41.9
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Model

Jina Embeddings V4 Vllm Retrieval

by jinaai jinaai/jina-embeddings-v4-vllm-retrieval
Free2AITools Nexus Index
41.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 50
P: Popularity 63
R: Recency 57
Q: Quality 65
Tech Context
3.75 Params
32.768K Ctx
Vital Performance
285.4K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 41.9 FNI Score
3.75B Params
32k Context
Hot 285.4K Downloads
8G GPU ~6GB Est. VRAM
Dense QWEN2_5_VLFORCONDITIONALGENERATION Architecture
Model Information Summary
Entity Passport
Registry ID jinaai/jina-embeddings-v4-vllm-retrieval
Provider huggingface
πŸ’Ύ

Compute Threshold

~5.3GB 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_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.}
}
APA Style
jinaai. (2026). Jina Embeddings V4 Vllm Retrieval [Model]. Free2AITools. https://huggingface.co/jinaai/jina-embeddings-v4-vllm-retrieval

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run jina-embeddings-v4-vllm-retrieval
πŸ€— HF Download
huggingface-cli download jinaai/jina-embeddings-v4-vllm-retrieval
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) 50
Popularity (P) 63
Recency (R) 57
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Jina Embeddings V4 Vllm Retrieval: Authority (A:50), Popularity (P:63), Recency (R:57), 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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Deployment reference

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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
285.4KDownloads
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-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

βš™οΈ Technical Specs

architecture
Qwen2_5_VLForConditionalGeneration
params billions
3.75
context length
32,768
pipeline tag
visual-document-retrieval
vram gb
5.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
285,378
stars
0
forks
0

Data indexed from public sources. Updated daily.