Gaming Optimizer vs OpenGameBoost

Gaming Optimizer is a free, MIT-licensed Windows app for managing CPU affinity in games and background processes. It can assign games to fast cores and demote background processes, but CPU pinning is off by default and changes do not occur until it is enabled. The app says it restores altered processes and system settings when a game closes. Its dashboard shows CPU and GPU metrics, network activity, ping and jitter, bottleneck classifications and process zones. It detects game launches through WMI and scans Steam, Epic Games, GOG, Ubisoft Connect and EA App libraries. Per-game reports include average and peak CPU and GPU metrics and bottleneck breakdowns, with a cumulative sessions.csv file. An optional setting locks NVIDIA graphics clocks while a game runs and resets them afterward. The maker says there is no telemetry, analytics or update checking; the only outbound connection is a configurable latency ping. It requires Windows 10 version 1809 or Windows 11, an x64 processor and administrator rights. The README describes ZIP distribution without an installer, while the Releases page lists no releases.

OpenGameBoost is a free, open-source gaming optimizer for 64-bit Windows 10 and Windows 11. Game Mode can suspend Explorer, browsers, and game launchers to free CPU and RAM, then resume them instantly when deactivated. The application can flush unused process memory, switch to the High Performance power plan, change network settings by disabling Nagle’s algorithm and NetBIOS, and adjust game GPU scheduling priority through registry changes. Automatic detection can activate Game Mode when supported games launch; the listed detection catalog contains 18 games, including Call of Duty, Fortnite, Apex Legends, Counter-Strike 2, Valorant, League of Legends, and Minecraft. Supported launchers include Steam, Epic, Battle.net, EA, Ubisoft Connect, and GOG. Supported browsers include Chrome, Firefox, Edge, Opera, and Brave. Administrator privileges are required for full functionality. Downloads come from the Releases page; source setup requires Python 3.9 or newer. Changes are described as reversible.