🧠
Model

Longcat Audiodit 3.5b Fp8 Backup

by 9r4n4y hf-model--9r4n4y--longcat-audiodit-3.5b-fp8-backup
Nexus Index
37.5 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 2
R: Recency 100
Q: Quality 50
Tech Context
3.5 Params
4.096K Ctx
Vital Performance
25 DL / 30D
0.0%
Audited 37.5 FNI Score
3.5B Params
4k Context
25 Downloads
8G GPU ~4GB Est. VRAM
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--9r4n4y--longcat-audiodit-3.5b-fp8-backup
License MIT
Provider huggingface
💾

Compute Threshold

~3.9GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{hf_model__9r4n4y__longcat_audiodit_3.5b_fp8_backup,
  author = {9r4n4y},
  title = {Longcat Audiodit 3.5b Fp8 Backup Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/9r4n4y/longcat-audiodit-3.5b-fp8-backup}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
9r4n4y. (2026). Longcat Audiodit 3.5b Fp8 Backup [Model]. Free2AITools. https://huggingface.co/9r4n4y/longcat-audiodit-3.5b-fp8-backup

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run longcat-audiodit-3.5b-fp8-backup
🤗 HF Download
huggingface-cli download 9r4n4y/longcat-audiodit-3.5b-fp8-backup
đŸ“Ļ Install Lib
pip install -U transformers

âš–ī¸ Nexus Index V2.0

37.5
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 2
Recency (R) 100
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Longcat Audiodit 3.5b Fp8 Backup: Semantic (S:50), Authority (A:0), Popularity (P:2), Recency (R:100), Quality (Q:50).

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
25Downloads
🔄 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--9r4n4y--longcat-audiodit-3.5b-fp8-backup
slug
9r4n4y--longcat-audiodit-3.5b-fp8-backup
source
huggingface
author
9r4n4y
license
MIT
tags
transformers, safetensors, audiodit, comfyui, text-to-speech, zh, en, license:mit, endpoints_compatible, region:us

âš™ī¸ Technical Specs

architecture
null
params billions
3.5
context length
4,096
pipeline tag
text-to-speech
vram gb
3.9
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
25
stars
0
forks
0

Data indexed from public sources. Updated daily.