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Kiel 3.4 Omni model by kiel2
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Model

Kiel 3.4 Omni

by kiel2 kiel2/kiel-3.4-omni
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 65
Tech Context
2.09 Params
4.096K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 2.09B Params
4k Context
0 Downloads
8G GPU ~3GB Est. VRAM
Dense MULTIMODALITYCAUSALLM Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID kiel2/kiel-3.4-omni
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.9GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{kiel2_kiel_3_4_omni,
  author = {kiel2},
  title = {Kiel 3.4 Omni Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/kiel2/kiel-3.4-Omni}},
  note = {Accessed via Free2AITools.}
}
APA Style
kiel2. (2026). Kiel 3.4 Omni [Model]. Free2AITools. https://huggingface.co/kiel2/kiel-3.4-Omni

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run kiel-3.4-omni
πŸ€— HF Download
huggingface-cli download kiel2/kiel-3.4-omni

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) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Kiel 3.4 Omni: Authority (A:0), Popularity (P:0), 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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⚠️ 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--kiel2--kiel-3.4-omni
slug
kiel2--kiel-3.4-omni
source
huggingface
author
kiel2
license
MIT
tags
safetensors, multi_modality, janus, multimodal, kieltech, power-engineering, custom-code, image-text-to-text, conversational, custom_code, en, license:mit, region:us

βš™οΈ Technical Specs

architecture
MultiModalityCausalLM
params billions
2.09
context length
4,096
pipeline tag
image-text-to-text
vram gb
2.9
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.