🧠
Model

Tonka Gemma4 E2b Merged Q4 K M Gguf

by idromerom714 hf-model--idromerom714--tonka-gemma4-e2b-merged-q4_k_m-gguf
Nexus Index
35.5 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 30
Tech Context
2 Params
4.096K Ctx
Vital Performance
0 DL / 30D
0.0%
Audited 35.5 FNI Score
Tiny 2B Params
4k Context
0 Downloads
8G GPU ~3GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID hf-model--idromerom714--tonka-gemma4-e2b-merged-q4_k_m-gguf
Provider huggingface
💾

Compute Threshold

~2.8GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{hf_model__idromerom714__tonka_gemma4_e2b_merged_q4_k_m_gguf,
  author = {idromerom714},
  title = {Tonka Gemma4 E2b Merged Q4 K M Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/idromerom714/tonka-gemma4-e2b-merged-q4_k_m-gguf}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
idromerom714. (2026). Tonka Gemma4 E2b Merged Q4 K M Gguf [Model]. Free2AITools. https://huggingface.co/idromerom714/tonka-gemma4-e2b-merged-q4_k_m-gguf

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run tonka-gemma4-e2b-merged-q4_k_m-gguf
🤗 HF Download
huggingface-cli download idromerom714/tonka-gemma4-e2b-merged-q4_k_m-gguf

âš–ī¸ Nexus Index V2.0

35.5
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 30

đŸ’Ŧ Index Insight

FNI V2.0 for Tonka Gemma4 E2b Merged Q4 K M Gguf: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), Quality (Q:30).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

Technical Deep Dive

âš 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.
🔄 Daily sync (03:00 UTC)

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

📊 FNI Methodology 📚 Knowledge Baseâ„šī¸ Verify with original source

đŸ›Ąī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--idromerom714--tonka-gemma4-e2b-merged-q4_k_m-gguf
slug
idromerom714--tonka-gemma4-e2b-merged-q4_k_m-gguf
source
huggingface
author
idromerom714
license
tags
gguf, llama-cpp, gguf-my-repo, base_model:idromerom714/tonka-gemma4-e2b-merged, endpoints_compatible, region:us, conversational

âš™ī¸ Technical Specs

architecture
null
params billions
2
context length
4,096
pipeline tag
vram gb
2.8
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.