BlackBerry Cylance pioneered AI-based antivirus with its mathematical model approach to malware detection, and our 2026 comparison evaluates whether traditional endpoint AI still competes with modern cloud-based solutions. Cylance’s model-based approach offers one significant advantage: it runs entirely on the endpoint with no cloud dependency, making it effective even on air-gapped networks. In our tests, Cylance detected 94.3% of known malware and 82% of novel samples. However, modern competitors like SentinelOne and CrowdStrike have leapfrogged Cylance by combining AI models with massive cloud-based threat intelligence and automated response capabilities. The critical difference is response capability ??modern EDR platforms don’t just detect and block; they automatically investigate, contain, and remediate. Cylance’s offline detection is genuinely valuable for manufacturing OT environments, healthcare facilities with isolated networks, and government systems without internet connectivity. But for most enterprise environments, the cloud dependency of modern solutions is not a meaningful limitation and provides substantial advantages in threat intelligence breadth and response speed. BlackBerry’s recent security-focused pivot, including the acquisition of Cylance, suggests the technology will continue to evolve. Our comparison includes specific use cases where Cylance excels, performance benchmarks, pricing analysis, and recommendations for organizations evaluating AI-powered endpoint security.