Amp Locker vs Neural Amp Modeler

Amp Locker is a guitar sound-shaping suite built around virtual amps, stompboxes, cabinets, and effects. It runs on Windows, macOS, and Linux as a standalone app or plug-in. The free download includes the Prestige 1950 amp, seven FX pedals, seven rack effects, and 11 three-dimensional cabinets with 11 microphones. Users can adjust pedals and rack effects and move microphones around the cabinets. Other listed tools include double tracking emulation, MIDI support, an IR loader, and the 3D Cab Impact algorithm. The stated plug-in formats are AU, VST3, RTAS, and AAX. More gear modules can be licensed individually inside the application, and optional extras include DSP and AI amp profile players. The $5 a month subscription covers Amp Locker and Mix Locker modules, but excludes 3D Cab add-on packs and signature amp sims such as Berry Amp. Cancelling the subscription deactivates the plug-in. The license limits installation to machines where the licensee is the sole user and bars machines that could redistribute plug-ins to other computers.

Neural Amp Modeler (NAM) uses deep learning to create models of guitar amplifiers and pedals. The project is free and open source, with three code repositories under permissive licenses that are open to contributions. Users can train models online in Google Colab or install the Python-based trainer locally from PyPI. The Gateway plugin loads and plays snapshot models of gear, while ParametricOD demonstrates modeling across an overdrive's knobs and switches. The plugin repository produces VST3 and AU plugins as well as a standalone desktop application. Models can be shared through TONE3000, a community-organized online library. NAM runs on Windows, macOS, Linux, Raspberry Pi, embedded systems, and websites. Existing A1 models remain supported in NeuralAmpModelerCore and NeuralAmpModelerPlugin. Builders can incorporate NAM's open-source modeling technology into their own products. The training code depends on PyTorch Lightning; version 0.12.3 excludes compromised Lightning versions 2.6.2 and 2.6.3.