🧠
Coreml Juggernaut Xl V9 8bit model by EE7777777
⭐ 37.4
🧠
Model

Coreml Juggernaut Xl V9 8bit

by EE7777777 ee7777777/coreml-juggernaut-xl-v9-8bit
Free2AITools Nexus Index
37.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 98
Q: Quality 50
Tech Context
8 Params
4.096K Ctx
Vital Performance —
Source β†’

Task categories from upstream metadata

🎨AI Art Gen

Technical Constraints

Experimental / High Latency
Low FNI signal 37.4 FNI Score
8B Params
4k Context
0 Downloads
8G GPU ~8GB Est. VRAM
Restricted CREATIVEML License
Model Information Summary
Entity Passport
Registry ID ee7777777/coreml-juggernaut-xl-v9-8bit
License creativeml-openrail-m
Provider huggingface
πŸ’Ύ

Compute Threshold

~7.3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ee7777777_coreml_juggernaut_xl_v9_8bit,
  author = {EE7777777},
  title = {Coreml Juggernaut Xl V9 8bit Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/EE7777777/coreml-juggernaut-xl-v9-8bit}},
  note = {Accessed via Free2AITools.}
}
APA Style
EE7777777. (2026). Coreml Juggernaut Xl V9 8bit [Model]. Free2AITools. https://huggingface.co/EE7777777/coreml-juggernaut-xl-v9-8bit

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run coreml-juggernaut-xl-v9-8bit
πŸ€— HF Download
huggingface-cli download ee7777777/coreml-juggernaut-xl-v9-8bit

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 0
Recency (R) 98
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Coreml Juggernaut Xl V9 8bit: Authority (A:0), Popularity (P:0), Recency (R:98), Quality (Q:50). 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.
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--ee7777777--coreml-juggernaut-xl-v9-8bit
slug
ee7777777--coreml-juggernaut-xl-v9-8bit
source
huggingface
author
EE7777777
license
creativeml-openrail-m
tags
core-ml, coreml, stable-diffusion, apple-silicon, ios, quantized, text-to-image, base_model:rundiffusion/juggernaut-xl-v9, base_model:finetune:rundiffusion/juggernaut-xl-v9, license:creativeml-openrail-m, region:us

βš™οΈ Technical Specs

params billions
8
context length
4,096
pipeline tag
text-to-image
vram gb
7.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0

Data indexed from public sources. Updated daily.