Kofi Mensah
Inference Economics & Hardware Architect
Kofi Mensah is a hardware architect and AI infrastructure specialist focused on optimizing inference costs for on-device and local-first AI deployments. With expertise in CPU/GPU architectures, Kofi analyzes real-world performance trade-offs between commercial cloud AI services and sovereign, self-hosted models running on consumer and enterprise hardware (Apple Silicon, NVIDIA, AMD, custom ARM systems). He quantifies the total cost of ownership for AI infrastructure and evaluates which deployment models (cloud, hybrid, on-device) make economic sense for different workloads and use cases. Kofi's technical analysis covers model quantization, inference optimization techniques (llama.cpp, vLLM), and hardware acceleration for language models, vision models, and multimodal systems. At Vucense, Kofi provides detailed cost analysis and performance benchmarks to help developers understand the real economics of sovereign AI.