🧠
Gemma 3n E2b It Gguf model by Ggml Org
⭐ 35.7
🧠
Model

Gemma 3n E2b It Gguf

by Ggml Org ggml-org/gemma-3n-e2b-it-gguf
Free2AITools Nexus Index
35.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 49
P: Popularity 40
R: Recency 54
Q: Quality 65
Tech Context
2 Params
4.096K Ctx
Vital Performance
5.6K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 35.7 FNI Score
Tiny 2B Params
4k Context
5.6K Downloads
8G GPU ~3GB Est. VRAM
Restricted GEMMA License
Model Information Summary
Entity Passport
Registry ID ggml-org/gemma-3n-e2b-it-gguf
License Gemma
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{ggml_org_gemma_3n_e2b_it_gguf,
  author = {Ggml Org},
  title = {Gemma 3n E2b It Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ggml-org/gemma-3n-E2B-it-GGUF}},
  note = {Accessed via Free2AITools.}
}
APA Style
Ggml Org. (2026). Gemma 3n E2b It Gguf [Model]. Free2AITools. https://huggingface.co/ggml-org/gemma-3n-E2B-it-GGUF

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma-3n-e2b-it-gguf
πŸ€— HF Download
huggingface-cli download ggml-org/gemma-3n-e2b-it-gguf

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 49
Popularity (P) 40
Recency (R) 54
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gemma 3n E2b It Gguf: Authority (A:49), Popularity (P:40), Recency (R:54), 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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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.

Social Proof

HuggingFace Hub
5.6KDownloads
Hub Discussions
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--ggml-org--gemma-3n-e2b-it-gguf
slug
ggml-org--gemma-3n-e2b-it-gguf
source
huggingface
author
Ggml Org
license
Gemma
tags
gguf, base_model:google/gemma-3n-e2b-it, base_model:quantized:google/gemma-3n-e2b-it, license:gemma, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

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

πŸ“Š Engagement & Metrics

downloads
5,631
stars
0
forks
0

Data indexed from public sources. Updated daily.