🧠
Firered Ocr Exl3 model by cgus
⭐ 37.6
🧠
Model

Firered Ocr Exl3

by cgus hf-model--cgus--firered-ocr-exl3
Free2AITools Nexus Index
37.6 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 2
R: Recency 98
Q: Quality 50
Tech Context
1.19 Params
32.768K Ctx
Vital Performance
20 DL / 30D
0.0%
Source →
Audited 37.6 FNI Score
Tiny 1.19B Params
32k Context
20 Downloads
8G GPU ~4GB Est. VRAM
Dense QWEN3VLFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--cgus--firered-ocr-exl3
License Apache-2.0
Provider huggingface
💾

Compute Threshold

~3.4GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__cgus__firered_ocr_exl3,
  author = {cgus},
  title = {Firered Ocr Exl3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/cgus/FireRed-OCR-exl3}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
cgus. (2026). Firered Ocr Exl3 [Model]. Free2AITools. https://huggingface.co/cgus/FireRed-OCR-exl3

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run firered-ocr-exl3
🤗 HF Download
huggingface-cli download cgus/firered-ocr-exl3

⚖ī¸ Free2AITools Nexus Index V2.0

Methodology Index Protocol
Semantic (S) 50
Authority (A) 0
Popularity (P) 2
Recency (R) 98
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Firered Ocr Exl3: Semantic (S:50), Authority (A:0), Popularity (P:2), Recency (R:98), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

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⚡

Deployment Guide

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Technical Deep Dive

⚠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
20Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--cgus--firered-ocr-exl3
slug
cgus--firered-ocr-exl3
source
huggingface
author
cgus
license
Apache-2.0
tags
safetensors, qwen3_vl, image-to-text, arxiv:2603.01840, base_model:fireredteam/firered-ocr, base_model:quantized:fireredteam/firered-ocr, license:apache-2.0, 4-bit, exl3, region:us

⚙ī¸ Technical Specs

architecture
Qwen3VLForConditionalGeneration
params billions
1.19
context length
32,768
pipeline tag
image-to-text
vram gb
3.4
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
20
stars
0
forks
null

Data indexed from public sources. Updated daily.