Benchmarking of GPT-OSS 20B Inference reveals that running AI models on-premises using older GPUs can deliver performance comparable to cloud-based solutions, challenging the notion that high costs are necessary for enterprise-grade AI. The study found that using SGLang on NVIDIA RTX GPUs resulted in significantly higher success rates, throughput, and reduced latency compared to Ollama, indicating that sovereignty in AI does not compromise performance. The benchmark highlights the economic advantage of owning infrastructure, which allows for control over data pipelines and model behavior, making it a viable option for companies concerned with data privacy and cost-efficiency. Furthermore, the potential of confidential computing is presented as the next step in ensuring data privacy without sacrificing performance, suggesting that organizations can maintain control over their AI without relying on cloud services.