🧠
Llama 4 Scout 17b 16e Instruct Quantized.w4a16 model by RedHatAI
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Model

Llama 4 Scout 17b 16e Instruct Quantized.w4a16

by RedHatAI redhatai/llama-4-scout-17b-16e-instruct-quantized.w4a16
Free2AITools Nexus Index
57.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 46
P: Popularity 43
R: Recency 100
Q: Quality 65
Tech Context
109.44 Params
8.192K Ctx
Vital Performance
9.1K DL / 30D
Source →
Audited 57 FNI Score
Massive 109.44B Params
8k Context
9.1K Downloads
H100+ ~85GB Est. VRAM
Dense LLAMA4FORCONDITIONALGENERATION Architecture
Restricted LLAMA4 License
Model Information Summary
Entity Passport
Registry ID redhatai/llama-4-scout-17b-16e-instruct-quantized.w4a16
License llama4
Provider huggingface
💾

Compute Threshold

~84.6GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization. [Multi-GPU / Unified Memory Required]

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Cite this model

Academic & Research Attribution

BibTeX 
@misc{redhatai_llama_4_scout_17b_16e_instruct_quantized_w4a16,
  author = {RedHatAI},
  title = {Llama 4 Scout 17b 16e Instruct Quantized.w4a16 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/RedHatAI/Llama-4-Scout-17B-16E-Instruct-quantized.w4a16}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
RedHatAI. (2026). Llama 4 Scout 17b 16e Instruct Quantized.w4a16 [Model]. Free2AITools. https://huggingface.co/RedHatAI/Llama-4-Scout-17B-16E-Instruct-quantized.w4a16

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download redhatai/llama-4-scout-17b-16e-instruct-quantized.w4a16

⚖ī¸ Free2AITools Nexus Index V2.0

Methodology Index Protocol
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 46
Popularity (P) 43
Recency (R) 100
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Llama 4 Scout 17b 16e Instruct Quantized.w4a16: Authority (A:46), Popularity (P:43), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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⚠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.

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📝 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
9.1KDownloads
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--redhatai--llama-4-scout-17b-16e-instruct-quantized.w4a16
slug
redhatai--llama-4-scout-17b-16e-instruct-quantized.w4a16
source
huggingface
author
RedHatAI
license
llama4
tags
safetensors, llama4, facebook, meta, pytorch, llama, neuralmagic, redhat, llmcompressor, quantized, w4a16, int4, conversational, compressed-tensors, image-text-to-text, ar, de, en, es, fr, hi, id, it, pt, th, tl, vi, license:llama4, region:us

⚙ī¸ Technical Specs

architecture
Llama4ForConditionalGeneration
params billions
109.44
context length
8,192
pipeline tag
image-text-to-text
vram gb
84.6
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
9,127
stars
null
forks
null

Data indexed from public sources. Updated daily.