🧠
Gemma 4 31b It Awq model by QuantTrio
⭐ 46
🧠
Model

Gemma 4 31b It Awq

by QuantTrio hf-model--quanttrio--gemma-4-31b-it-awq
Nexus Index
46.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 56
R: Recency 98
Q: Quality 65
Tech Context
31 Params
4.096K Ctx
Vital Performance
68.0K DL / 30D
0.0%
Source →
Audited 46 FNI Score
31B Params
4k Context
Hot 68.0K Downloads
H100+ ~26GB Est. VRAM
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--quanttrio--gemma-4-31b-it-awq
License Apache-2.0
Provider huggingface
💾

Compute Threshold

~25.8GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__quanttrio__gemma_4_31b_it_awq,
  author = {QuantTrio},
  title = {Gemma 4 31b It Awq Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/quanttrio/gemma-4-31b-it-awq}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
QuantTrio. (2026). Gemma 4 31b It Awq [Model]. Free2AITools. https://huggingface.co/quanttrio/gemma-4-31b-it-awq

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run gemma-4-31b-it-awq
🤗 HF Download
huggingface-cli download quanttrio/gemma-4-31b-it-awq
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
46.0
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 56
Recency (R) 98
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Gemma 4 31b It Awq: Semantic (S:50), Authority (A:0), Popularity (P:56), Recency (R:98), Quality (Q:65).

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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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
68.0KDownloads
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--quanttrio--gemma-4-31b-it-awq
slug
quanttrio--gemma-4-31b-it-awq
source
huggingface
author
QuantTrio
license
Apache-2.0
tags
transformers, safetensors, gemma4, image-text-to-text, vllm, awq, conversational, base_model:google/gemma-4-31b-it, base_model:quantized:google/gemma-4-31b-it, license:apache-2.0, endpoints_compatible, 4-bit, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
31
context length
4,096
pipeline tag
image-text-to-text
vram gb
25.8
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
68,043
stars
0
forks
0

Data indexed from public sources. Updated daily.