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Fishaudio S2 Pro 8bit Mlx model by appautomaton
⭐ 39.7
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Model

Fishaudio S2 Pro 8bit Mlx

by appautomaton appautomaton/fishaudio-s2-pro-8bit-mlx
Free2AITools Nexus Index
39.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 39
P: Popularity 21
R: Recency 98
Q: Quality 65
Tech Context
4.56 Params
4.096K Ctx
Vital Performance
559 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.7 FNI Score
4.56B Params
4k Context
559 Downloads
8G GPU ~5GB Est. VRAM
Dense FISH_QWEN3_OMNI Architecture
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID appautomaton/fishaudio-s2-pro-8bit-mlx
License Other
Provider huggingface
πŸ’Ύ

Compute Threshold

~4.7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{appautomaton_fishaudio_s2_pro_8bit_mlx,
  author = {appautomaton},
  title = {Fishaudio S2 Pro 8bit Mlx Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/appautomaton/fishaudio-s2-pro-8bit-mlx}},
  note = {Accessed via Free2AITools.}
}
APA Style
appautomaton. (2026). Fishaudio S2 Pro 8bit Mlx [Model]. Free2AITools. https://huggingface.co/appautomaton/fishaudio-s2-pro-8bit-mlx

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run fishaudio-s2-pro-8bit-mlx
πŸ€— HF Download
huggingface-cli download appautomaton/fishaudio-s2-pro-8bit-mlx

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 39
Popularity (P) 21
Recency (R) 98
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Fishaudio S2 Pro 8bit Mlx: Authority (A:39), Popularity (P:21), Recency (R:98), 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.

Social Proof

HuggingFace Hub
559Downloads
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--appautomaton--fishaudio-s2-pro-8bit-mlx
slug
appautomaton--fishaudio-s2-pro-8bit-mlx
source
huggingface
author
appautomaton
license
Other
tags
mlx, safetensors, fish_qwen3_omni, tts, speech, fishaudio, fish-s2-pro, quantized, int8, apple-silicon, bundled-codec, text-to-speech, base_model:fishaudio/s2-pro, base_model:quantized:fishaudio/s2-pro, license:other, region:us

βš™οΈ Technical Specs

architecture
fish_qwen3_omni
params billions
4.56
context length
4,096
pipeline tag
text-to-speech
vram gb
4.7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
559
stars
0
forks
0

Data indexed from public sources. Updated daily.