Gjalla vs Neural Amp Modeler

Gjalla is a free, open-source guitar amp simulator for black metal and other raw styles. Sognevo, a one-person project making dark-music audio plugins, provides it for Windows, macOS, and Linux as VST3, CLAP, and, on macOS, AU, plus a standalone application. The processing chain includes input trim, noise gate, pedal, preamp, tone stack, power section, presence, cabinet, frost, and output trim. Its pedal offers 90s distortion, HM-2-style chainsaw, and starved-transistor fuzz voicings. Three analytic cabinets are included; WAV or AIFF impulse responses up to two seconds can be loaded, or the cabinet can be disabled for an external loader. Six factory presets, meters, editable knob values, undo and redo, tooltips, and a resizable interface are provided. Host latency is reported as six samples, stated as 0.13 ms at 48 kHz. There is no packaged release yet, so users must build from source or follow GitHub releases. A build requires Git, CMake 3.22 or later, and a C++20 compiler. Gjalla is GPLv3-or-later and has no telemetry, network access, update checks, or accounts.

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.