How does an air-gapped local GPU LLM ensure DPDP compliance for law firms?

All model execution, embeddings, and document parsing run 100% inside your physical GPU hardware with zero outbound internet endpoints, ensuring zero cloud PII data leakage and 100% DPDP Act compliance.

What GPU hardware is needed to run a 70B open-weights model locally?

A single NVIDIA RTX 6000 Ada (48GB VRAM) or a dual RTX 4090 system (48GB combined VRAM) runs AWQ / GGUF Q4_K_M 70B models at 25+ tokens per second with 32K context windows.

Back to Portfolio

Air-Gapped Private GPU Infrastructure

Local GPU LLM Quantization
& MCP Legal/Compliance Servers

Run 70B parameter open-weights models (Qwen 2.5, Llama 3.3) 100% air-gapped on workstation GPUs (RTX 6000 Ada 48GB or dual RTX 4090). Eliminate monthly SaaS API bills while maintaining complete compliance under DPDP Act and advocate-client privilege laws.

Schedule AI Architecture Audit Read Engineering Case Study →

70B Params

Open Weights Model

100% Offline

Air-Gapped Privacy

25.4 Tok/s

70B Inference Speed

MCP Protocol

Local Vector RAG

Local AI Engineering Stack

AWQ & GGUF 4-Bit Quantization

Compresses 140GB FP16 model weights down to 38.5GB VRAM, allowing full 70B parameter inference to run smoothly on workstation GPUs without memory overflow.

DPDP Act Compliance

Zero third-party API data processors. Confidential client records, contracts, and internal communications never leave your physical premises.

Model Context Protocol (MCP) Server

Implements Anthropic MCP specification connecting local vector stores (ChromaDB / pgvector) to legal assistant UIs over secure local stdio streams.

FlashAttention-2 & PagedAttention

vLLM kernel optimizations eliminate KV-cache memory fragmentation, supporting dynamic 32,768 context windows and concurrent local multi-user sessions.

Frequently Asked Questions

Can local 70B LLMs match cloud SaaS AI models in contract analysis accuracy?

Yes. Qwen 2.5 70B Instruct and Llama 3.3 70B score at par with GPT-4o on legal reasoning and document extraction tasks when paired with localized RAG.

What is the upfront hardware setup cost for an air-gapped GPU server?

A workstation equipped with dual RTX 4090 GPUs (48GB VRAM) costs ~$4,500 - $6,500 as a one-time capital expense, replacing recurring $1,000+/month SaaS API bills forever.

Build Your Air-Gapped Local GPU AI Server

Eliminate cloud data leakage liabilities under DPDP. Deploy 100% private 70B open-weights AI workstations today.

Consult Local AI Architect