LLaMA 3 is an open-source AI model developed by Meta. It can be deployed on-premises with the right GPU hardware for private, secure AI inference.

How much VRAM does LLaMA 3 require?

VRAM requirements for LLaMA 3 depend on the quantization level. Full-precision models need more VRAM, while quantized versions (Q4, Q5, Q8) can run on consumer GPUs. See our VRAM requirements table for specific recommendations.

Can I run LLaMA 3 locally?

Yes. LLaMA 3 can be run locally using frameworks like Ollama or vLLM. Petronella Technology Group builds GPU-accelerated workstations and servers optimized for local AI model deployment.

What GPU do I need for LLaMA 3?

The recommended GPU depends on the model size and quantization. For smaller quantized versions, an AMD Radeon or NVIDIA RTX GPU with 16-24 GB VRAM may suffice. For full-precision or larger variants, enterprise GPUs like the AMD Instinct MI300X or NVIDIA A100 are recommended.

Does Petronella help deploy LLaMA 3?

Yes. Petronella Technology Group provides end-to-end AI deployment services including hardware selection, system configuration, model optimization, and ongoing support. Contact us to discuss your LLaMA 3 deployment needs.

Open-Source AI Model

LLaMA 3

Name: LLaMA 3
Author: Meta

Developed by Meta

Local AI Deployment Experts 24+ Years IT Infrastructure GPU Hardware In Stock

Key Capabilities

State-of-the-art open-weight language understanding
Multilingual support (30+ languages)
128K context window for long document processing
Tool use and function calling
Strong code generation and reasoning

VRAM Requirements by Quantization

Choose the right GPU based on your performance and quality needs.

Model / Quantization	VRAM Required
8B FP16	16GB
70B FP16	140GB
70B Q4	40GB
405B FP16	810GB
405B Q4	230GB

Use Cases

LLaMA 3 (8B, 70B, 405B) can be deployed for enterprise AI applications including document processing, code generation, data analysis, and conversational AI. License: Meta LLaMA 3 Community License (open-weight, commercial use allowed).

Run LLaMA 3 with Petronella

PTG builds turnkey LLaMA 3 inference servers and workstations. Run the 405B model on DGX hardware with zero cloud dependency - ideal for CMMC and HIPAA environments requiring air-gapped AI.

Recommended Hardware

Model Size	Recommended GPU
8B	RTX 5080 (16GB) or RTX PRO 4000 (24GB)
70B	RTX PRO 6000 Blackwell (96GB) or 2x RTX 5090 (64GB)
405B	DGX Spark (128GB) or DGX Station GB300 (384GB)

Deploy LLaMA 3 On-Premises

Our team builds GPU-accelerated systems configured and optimized for LLaMA 3. Private, secure, and fully under your control.

Talk to an AI Infrastructure Expert Browse AI Hardware

LLaMA 3

⚡Key Capabilities

📌VRAM Requirements by Quantization

🚀Use Cases