Architectures built forSOC 2HIPAAGDPREU AI Act

Enterprise Local AI, Private RAG & Compliance Benchmarks

VRAM and throughput estimates, private RAG reference architectures, and playbooks designed to support SOC 2, HIPAA, GDPR and EU AI Act workflows, for tax, legal and healthcare teams that can't send data to a public API.

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Qwen3-32B · Q4_K_M · 8k tokens

Formula estimate

Total VRAM required

21.5GB

Weights
18.5 GB
KV cache
2.0 GB
Overhead
1.0 GB
  • RTX 4090 24GB~24–37 tok/s
  • Mac mini M4 Pro 64GB~7–10 tok/s
Size your own model, quantization and context

Local LLM VRAM Calculator

2026 models

Total VRAM required

21.5GB

Weights
18.5 GB
KV cache
2.0 GB
Overhead
1.0 GB

Recommended local hardware

  • RTX 4090 24GB~24–37 tok/s
  • Mac mini M4 Pro 64GB~7–10 tok/s

Estimated single-user decode speed from memory bandwidth. Real throughput depends on runtime, drivers and prompt length.

Runs locally on RTX 4090 24GB — no cloud requiredCompare with a RunPod GPU pod →

Latest guides

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Phase 2: Regulated RAG & Compliance KD 4(easy). An editorial estimate entered by hand, not a live figure from Ahrefs, Semrush or similar tools.

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Phase 1: Local AI & Hardware KD 4(easy). An editorial estimate entered by hand, not a live figure from Ahrefs, Semrush or similar tools.

Qwen3-32B VRAM Calculator: FP16 vs Q8_0 vs Q4_K_M Memory Math and GPU Benchmarks

Qwen3-32B VRAM calculator: FP16, Q8_0 and Q4_K_M memory math, KV cache sizing, RTX 5090/4090 and Mac Studio estimates, plus Ollama and vLLM commands.