🧠
Model

Qwen Sea Lion V4 8b Vl

by aisingapore hf-model--aisingapore--qwen-sea-lion-v4-8b-vl
Nexus Index
54.5 Top 100%
S: Semantic 50
A: Authority 44
P: Popularity 31
R: Recency 100
Q: Quality 65
Tech Context
8 Params
4.096K Ctx
Vital Performance
1.7K DL / 30D
0.0%
Audited 54.5 FNI Score
8B Params
4k Context
1.7K Downloads
8G GPU ~8GB Est. VRAM
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--aisingapore--qwen-sea-lion-v4-8b-vl
License MIT
Provider huggingface
💾

Compute Threshold

~7.3GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{hf_model__aisingapore__qwen_sea_lion_v4_8b_vl,
  author = {aisingapore},
  title = {Qwen Sea Lion V4 8b Vl Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/aisingapore/qwen-sea-lion-v4-8b-vl}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
aisingapore. (2026). Qwen Sea Lion V4 8b Vl [Model]. Free2AITools. https://huggingface.co/aisingapore/qwen-sea-lion-v4-8b-vl

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run qwen-sea-lion-v4-8b-vl
🤗 HF Download
huggingface-cli download aisingapore/qwen-sea-lion-v4-8b-vl
đŸ“Ļ Install Lib
pip install -U transformers

âš–ī¸ Nexus Index V2.0

54.5
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 44
Popularity (P) 31
Recency (R) 100
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Qwen Sea Lion V4 8b Vl: Semantic (S:50), Authority (A:44), Popularity (P:31), Recency (R:100), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

Technical Deep Dive

âš ī¸ 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

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ 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
1.7KDownloads
🔄 Daily sync (03:00 UTC)

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

📊 FNI Methodology 📚 Knowledge Baseâ„šī¸ Verify with original source

đŸ›Ąī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--aisingapore--qwen-sea-lion-v4-8b-vl
slug
aisingapore--qwen-sea-lion-v4-8b-vl
source
huggingface
author
aisingapore
license
MIT
tags
transformers, safetensors, qwen3_vl, image-text-to-text, conversational, en, vi, id, th, my, ta, tl, ms, arxiv:2502.14301, arxiv:2311.07911, arxiv:2306.05685, arxiv:1910.09700, base_model:qwen/qwen3-vl-8b-instruct, base_model:finetune:qwen/qwen3-vl-8b-instruct, license:mit, endpoints_compatible, region:us

âš™ī¸ Technical Specs

architecture
null
params billions
8
context length
4,096
pipeline tag
image-text-to-text
vram gb
7.3
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
1,747
stars
0
forks
0

Data indexed from public sources. Updated daily.