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Bge Vl V1.5 Mmeb model by BAAI
⭐ 39.5
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Model

Bge Vl V1.5 Mmeb

by BAAI baai/bge-vl-v1.5-mmeb
Free2AITools Nexus Index
39.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 46
P: Popularity 11
R: Recency 87
Q: Quality 65
Tech Context
7.57 Params
4.096K Ctx
Vital Performance
148 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.5 FNI Score
7.57B Params
4k Context
148 Downloads
8G GPU ~7GB Est. VRAM
Dense LLAVANEXTFORCONDITIONALGENERATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID baai/bge-vl-v1.5-mmeb
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{baai_bge_vl_v1_5_mmeb,
  author = {BAAI},
  title = {Bge Vl V1.5 Mmeb Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/BAAI/BGE-VL-v1.5-mmeb}},
  note = {Accessed via Free2AITools.}
}
APA Style
BAAI. (2026). Bge Vl V1.5 Mmeb [Model]. Free2AITools. https://huggingface.co/BAAI/BGE-VL-v1.5-mmeb

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run bge-vl-v1.5-mmeb
πŸ€— HF Download
huggingface-cli download baai/bge-vl-v1.5-mmeb
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) 46
Popularity (P) 11
Recency (R) 87
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Bge Vl V1.5 Mmeb: Authority (A:46), Popularity (P:11), 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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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
148Downloads
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--baai--bge-vl-v1.5-mmeb
slug
baai--bge-vl-v1.5-mmeb
source
huggingface
author
BAAI
license
MIT
tags
sentence-transformers, safetensors, llava_next, multimodal-retrieval, embedding-model, sentence-similarity, custom_code, en, arxiv:2412.14475, base_model:llava-hf/llava-v1.6-mistral-7b-hf, license:mit, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
LlavaNextForConditionalGeneration
params billions
7.57
context length
4,096
pipeline tag
sentence-similarity
vram gb
7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
148
stars
0
forks
0

Data indexed from public sources. Updated daily.