🧠
Gemma 4 E2b It Gguf model by Ggml Org
⭐ 43.9
🧠
Model

Gemma 4 E2b It Gguf

by Ggml Org hf-model--ggml-org--gemma-4-e2b-it-gguf
Nexus Index
43.9 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 59
R: Recency 97
Q: Quality 30
Tech Context
2 Params
4.096K Ctx
Vital Performance
128.1K DL / 30D
0.0%
Source →
Audited 43.9 FNI Score
Tiny 2B Params
4k Context
Hot 128.1K Downloads
8G GPU ~3GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID hf-model--ggml-org--gemma-4-e2b-it-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__ggml_org__gemma_4_e2b_it_gguf,
  author = {Ggml Org},
  title = {Gemma 4 E2b It Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ggml-org/gemma-4-e2b-it-gguf}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Ggml Org. (2026). Gemma 4 E2b It Gguf [Model]. Free2AITools. https://huggingface.co/ggml-org/gemma-4-e2b-it-gguf

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run gemma-4-e2b-it-gguf
🤗 HF Download
huggingface-cli download ggml-org/gemma-4-e2b-it-gguf

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
43.9
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 59
Recency (R) 97
Quality (Q) 30

đŸ’Ŧ Index Insight

FNI V2.0 for Gemma 4 E2b It Gguf: Semantic (S:50), Authority (A:0), Popularity (P:59), Recency (R:97), Quality (Q:30).

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
128.1KDownloads
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--ggml-org--gemma-4-e2b-it-gguf
slug
ggml-org--gemma-4-e2b-it-gguf
source
huggingface
author
Ggml Org
license
tags
gguf, base_model:google/gemma-4-e2b-it, base_model:quantized:google/gemma-4-e2b-it, endpoints_compatible, region:us, conversational

⚙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
128,071
stars
0
forks
0

Data indexed from public sources. Updated daily.