🧠
Vieneu Tts V3 Turbo model by Pnnbao Ump
⭐ 60.8
🧠
Model

Vieneu Tts V3 Turbo

by Pnnbao Ump pnnbao-ump/vieneu-tts-v3-turbo
Free2AITools Nexus Index
60.8
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 51
P: Popularity 64
R: Recency 93
Q: Quality 65
Tech Context
0.13B Params
4.096K Ctx
Vital Performance
337.3K DL / 30D
Source β†’
Low FNI signal 60.8 FNI Score
Tiny 0.13B Params
4k Context
Hot 337.3K Downloads
8G GPU ~2GB Est. VRAM
Dense VIENEUV3TURBOFORTTS Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID pnnbao-ump/vieneu-tts-v3-turbo
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{pnnbao_ump_vieneu_tts_v3_turbo,
  author = {Pnnbao Ump},
  title = {Vieneu Tts V3 Turbo Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo}},
  note = {Accessed via Free2AITools.}
}
APA Style
Pnnbao Ump. (2026). Vieneu Tts V3 Turbo [Model]. Free2AITools. https://huggingface.co/pnnbao-ump/VieNeu-TTS-v3-Turbo

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run vieneu-tts-v3-turbo
πŸ€— HF Download
huggingface-cli download pnnbao-ump/vieneu-tts-v3-turbo

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 51
Popularity (P) 64
Recency (R) 93
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Vieneu Tts V3 Turbo: Authority (A:51), Popularity (P:64), Recency (R:93), 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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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
337.3KDownloads
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--pnnbao-ump--vieneu-tts-v3-turbo
slug
pnnbao-ump--vieneu-tts-v3-turbo
source
huggingface
author
Pnnbao Ump
license
Apache-2.0
tags
onnx, safetensors, vieneu_v3_turbo, voice-cloning, code-switching, podcast, emotion-control, 48khz, text-to-speech, vi, en, dataset:pnnbao-ump/vieneu-tts-10k-envi, license:apache-2.0, region:us

βš™οΈ Technical Specs

architecture
VieNeuV3TurboForTTS
params billions
0.13
context length
4,096
pipeline tag
text-to-speech
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
337,257
stars
null
forks
null

Data indexed from public sources. Updated daily.