🧠
Egotools 8b V3 3 model by egotools
⭐ 37.5
🧠
Model

Egotools 8b V3 3

by egotools egotools/egotools-8b-v3_3
Free2AITools Nexus Index
37.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 76
Q: Quality 50
Tech Context
8 Params
32.768K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.5 FNI Score
8B Params
32k Context
0 Downloads
24G GPU ~9GB Est. VRAM
Dense QWEN3VLFORCONDITIONALGENERATION Architecture
Model Information Summary
Entity Passport
Registry ID egotools/egotools-8b-v3_3
Provider huggingface
πŸ’Ύ

Compute Threshold

~8.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{egotools_egotools_8b_v3_3,
  author = {egotools},
  title = {Egotools 8b V3 3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/egotools/egotools-8b-v3_3}},
  note = {Accessed via Free2AITools.}
}
APA Style
egotools. (2026). Egotools 8b V3 3 [Model]. Free2AITools. https://huggingface.co/egotools/egotools-8b-v3_3

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run egotools-8b-v3_3
πŸ€— HF Download
huggingface-cli download egotools/egotools-8b-v3_3
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) 0
Popularity (P) 0
Recency (R) 76
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Egotools 8b V3 3: Authority (A:0), Popularity (P:0), Recency (R:76), 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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πŸš€ What's Next?

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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.
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--egotools--egotools-8b-v3_3
slug
egotools--egotools-8b-v3_3
source
huggingface
author
egotools
tags
transformers, safetensors, qwen3_vl, image-text-to-text, qwen3-vl, video-language-model, egocentric-video, ms-swift, sft, conversational, base_model:qwen/qwen3-vl-8b-instruct, base_model:finetune:qwen/qwen3-vl-8b-instruct, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Qwen3VLForConditionalGeneration
params billions
8
context length
32,768
pipeline tag
image-text-to-text
vram gb
8.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0

Data indexed from public sources. Updated daily.