🧠
Model

Qwen Sea Lion V4 32b It

by aisingapore hf-model--aisingapore--qwen-sea-lion-v4-32b-it
Nexus Index
55.6 Top 100%
S: Semantic 50
A: Authority 44
P: Popularity 38
R: Recency 100
Q: Quality 65
Tech Context
32 Params
4.096K Ctx
Vital Performance
4.5K DL / 30D
0.0%
Audited 55.6 FNI Score
32B Params
4k Context
4.5K Downloads
H100+ ~27GB Est. VRAM
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--aisingapore--qwen-sea-lion-v4-32b-it
License MIT
Provider huggingface
💾

Compute Threshold

~26.5GB 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_32b_it,
  author = {aisingapore},
  title = {Qwen Sea Lion V4 32b It Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/aisingapore/qwen-sea-lion-v4-32b-it}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
aisingapore. (2026). Qwen Sea Lion V4 32b It [Model]. Free2AITools. https://huggingface.co/aisingapore/qwen-sea-lion-v4-32b-it

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run qwen-sea-lion-v4-32b-it
🤗 HF Download
huggingface-cli download aisingapore/qwen-sea-lion-v4-32b-it
đŸ“Ļ Install Lib
pip install -U transformers

âš–ī¸ Nexus Index V2.0

55.6
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 44
Popularity (P) 38
Recency (R) 100
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Qwen Sea Lion V4 32b It: Semantic (S:50), Authority (A:44), Popularity (P:38), Recency (R:100), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
---

🚀 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
4.5KDownloads
🔄 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-v4-32b-it
slug
aisingapore--qwen-sea-lion-v4-32b-it
source
huggingface
author
aisingapore
license
MIT
tags
transformers, safetensors, qwen3, text-generation, conversational, en, zh, vi, id, th, fil, ta, ms, km, lo, my, arxiv:2502.14301, arxiv:2311.07911, arxiv:2306.05685, base_model:qwen/qwen3-32b, base_model:finetune:qwen/qwen3-32b, license:mit, text-generation-inference, endpoints_compatible, region:us

âš™ī¸ Technical Specs

architecture
null
params billions
32
context length
4,096
pipeline tag
text-generation
vram gb
26.5
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
4,536
stars
0
forks
0

Data indexed from public sources. Updated daily.