Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs
Want private AI without cloud risk or spend? This study shows SMEs can run production LLMs on NVIDIA Blackwell consumer GPUs (RTX 5060 Ti, 5070 Ti, 5090).
- Cost: $0.001–$0.04 per million tokens (electricity only) — 40–200x cheaper than budget cloud APIs.
- ROI: Hardware can pay for itself in under 4 months at ~30M tokens/day.
- Speed: RTX 5090 hits 3.5–4.6x more throughput than 5060 Ti and up to 21x lower RAG latency.
- Value: For high-concurrency APIs, budget GPUs give the best throughput-per-dollar with sub-second latency.
- Efficiency: NVFP4 quantization delivers ~1.6x throughput and 41% less energy, with only 2–4% quality loss.
- Limits: Latency-critical, long-context RAG still favors high-end cards.
Benchmarks span Qwen3-8B, Gemma3-12B/27B, GPT-OSS-20B; context up to 64k; and workloads like RAG, multi-LoRA agents, and busy APIs. The authors share deployment guidance and all data for reproducible SME setups.
Paper: https://arxiv.org/abs/2601.09527v1
Paper: https://arxiv.org/abs/2601.09527v1
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LLM SMEs GPUs Blackwell RTX5090 OnPrem Privacy MLOps Quantization RAG EdgeAI CostOptimization
