SOC 2HIPAAGDPREU AI Act
Enterprise Local AI, Private RAG & Compliance Benchmarks
Reproducible VRAM and throughput benchmarks, private RAG reference architectures, and compliance playbooks for tax, legal and healthcare teams that can't send data to a public API.
Local LLM VRAM Calculator
2026 modelsTotal 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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Docling vs PyMuPDF4LLM on financial statements and tax audit PDFs: speed, merged-cell table handling, licensing, Python code and local RAG tips.
Phase 1: Local AI & HardwareKD 4
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.