🧠
Higgs Tts V3 4b model by bosonai
⭐ 61.6
🧠
Model

Higgs Tts V3 4b

by bosonai bosonai/higgs-tts-v3-4b
Free2AITools Nexus Index
61.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 57
P: Popularity 57
R: Recency 100
Q: Quality 65
Tech Context
4.65 Params
4.096K Ctx
Vital Performance
86.1K DL / 30D
Source β†’
Low FNI signal 61.6 FNI Score
4.65B Params
4k Context
Hot 86.1K Downloads
8G GPU ~5GB Est. VRAM
Dense HIGGSMULTIMODALQWEN3FORCONDITIONALGENERATION Architecture
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID bosonai/higgs-tts-v3-4b
License Other
Provider huggingface
πŸ’Ύ

Compute Threshold

~4.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{bosonai_higgs_tts_v3_4b,
  author = {bosonai},
  title = {Higgs Tts V3 4b Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/bosonai/higgs-tts-v3-4b}},
  note = {Accessed via Free2AITools.}
}
APA Style
bosonai. (2026). Higgs Tts V3 4b [Model]. Free2AITools. https://huggingface.co/bosonai/higgs-tts-v3-4b

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run higgs-tts-v3-4b
πŸ€— HF Download
huggingface-cli download bosonai/higgs-tts-v3-4b
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) 57
Popularity (P) 57
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Higgs Tts V3 4b: Authority (A:57), Popularity (P:57), Recency (R:100), 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
86.1KDownloads
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--bosonai--higgs-tts-v3-4b
slug
bosonai--higgs-tts-v3-4b
source
huggingface
author
bosonai
license
Other
tags
qwen, text-generation, transformers, safetensors, higgs_multimodal_qwen3, text-to-speech, speech-generation, voice-agent, expressive-speech, controllable-tts, multilingual-tts, af, ar, as, ast, az, ba, be, bg, bn, bs, ca, ceb, ckb, cs, cy, da, de, el, en, eo, es, et, eu, fa, fi, fr, ga, gl, gu, ha, he, hi, hr, ht, hu, hy, id, is, it, jv, ka, kab, kam, kea, kk, kn, ko, ky, la, lb, lg, ln, lt, luo, lv, mhr, mi, mk, ml, mn, mr, ms, mt, ne, nl, no, nso, ny, oc, om, pa, pl, ps, pt, ro, ru, rw, sd, sk

βš™οΈ Technical Specs

architecture
HiggsMultimodalQwen3ForConditionalGeneration
params billions
4.65
context length
4,096
pipeline tag
text-to-speech
vram gb
4.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
86,146
stars
null
forks
null

Data indexed from public sources. Updated daily.