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Llama 3.3 70b Instruct Quantized.w4a16 model by RedHatAI
⭐ 54.6
🧠
Model

Llama 3.3 70b Instruct Quantized.w4a16

by RedHatAI redhatai/llama-3.3-70b-instruct-quantized.w4a16
Free2AITools Nexus Index
54.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 39
P: Popularity 40
R: Recency 100
Q: Quality 65
Tech Context
71.14 Params
8.192K Ctx
Vital Performance
6.0K DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue
Low FNI signal 54.6 FNI Score
71.14B Params
8k Context
6.0K Downloads
H100+ ~56GB Est. VRAM
Dense LLAMAFORCAUSALLM Architecture
Restricted LLAMA3.3 License
Model Information Summary
Entity Passport
Registry ID redhatai/llama-3.3-70b-instruct-quantized.w4a16
License llama3.3
Provider huggingface
πŸ’Ύ

Compute Threshold

~55.9GB VRAM

Interactive
Estimate fit
β–Ό

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

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{redhatai_llama_3_3_70b_instruct_quantized_w4a16,
  author = {RedHatAI},
  title = {Llama 3.3 70b Instruct Quantized.w4a16 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/RedHatAI/Llama-3.3-70B-Instruct-quantized.w4a16}},
  note = {Accessed via Free2AITools.}
}
APA Style
RedHatAI. (2026). Llama 3.3 70b Instruct Quantized.w4a16 [Model]. Free2AITools. https://huggingface.co/RedHatAI/Llama-3.3-70B-Instruct-quantized.w4a16

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run llama-3.3-70b-instruct-quantized.w4a16
πŸ€— HF Download
huggingface-cli download redhatai/llama-3.3-70b-instruct-quantized.w4a16

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 39
Popularity (P) 40
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Llama 3.3 70b Instruct Quantized.w4a16: Authority (A:39), Popularity (P:40), Recency (R:100), 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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Deployment reference

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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
6.0KDownloads
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--redhatai--llama-3.3-70b-instruct-quantized.w4a16
slug
redhatai--llama-3.3-70b-instruct-quantized.w4a16
source
huggingface
author
RedHatAI
license
llama3.3
tags
safetensors, llama, facebook, meta, llama-3, int4, vllm, chat, neuralmagic, llmcompressor, conversational, 4-bit precision, compressed-tensors, text-generation, en, de, fr, it, pt, hi, es, th, arxiv:2210.17323, base_model:meta-llama/llama-3.3-70b-instruct, license:llama3.3, region:us

βš™οΈ Technical Specs

architecture
LlamaForCausalLM
params billions
71.14
context length
8,192
pipeline tag
text-generation
vram gb
55.9
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
5,994
stars
null
forks
null

Data indexed from public sources. Updated daily.