🧠
Gemma 4 31b It 4bit model by NexVeridian
⭐ 39.4
🧠
Model

Gemma 4 31b It 4bit

by NexVeridian nexveridian/gemma-4-31b-it-4bit
Free2AITools Nexus Index
39.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 23
R: Recency 85
Q: Quality 65
Tech Context
30.7 Params
8.192K Ctx
Vital Performance
723 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39.4 FNI Score
30.7B Params
8k Context
723 Downloads
H100+ ~26GB Est. VRAM
Dense GEMMA4FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID nexveridian/gemma-4-31b-it-4bit
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~25.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{nexveridian_gemma_4_31b_it_4bit,
  author = {NexVeridian},
  title = {Gemma 4 31b It 4bit Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/NexVeridian/gemma-4-31B-it-4bit}},
  note = {Accessed via Free2AITools.}
}
APA Style
NexVeridian. (2026). Gemma 4 31b It 4bit [Model]. Free2AITools. https://huggingface.co/NexVeridian/gemma-4-31B-it-4bit

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run gemma-4-31b-it-4bit
πŸ€— HF Download
huggingface-cli download nexveridian/gemma-4-31b-it-4bit

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 33
Popularity (P) 23
Recency (R) 85
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Gemma 4 31b It 4bit: Authority (A:33), Popularity (P:23), Recency (R:85), 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.

Social Proof

HuggingFace Hub
723Downloads
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--nexveridian--gemma-4-31b-it-4bit
slug
nexveridian--gemma-4-31b-it-4bit
source
huggingface
author
NexVeridian
license
Apache-2.0
tags
mlx, safetensors, gemma4, text-generation, conversational, base_model:google/gemma-4-31b-it, base_model:quantized:google/gemma-4-31b-it, license:apache-2.0, 4-bit, region:us

βš™οΈ Technical Specs

architecture
Gemma4ForConditionalGeneration
params billions
30.7
context length
8,192
pipeline tag
text-generation
vram gb
25.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
723
stars
0
forks
0

Data indexed from public sources. Updated daily.