AmpKnob BDH III vs Neural Amp Modeler
AmpKnob BDH III
bogrendigital.com
Neural Amp Modeler
neuralampmodeler.comSide by side
| Figure | AmpKnob BDH III | Neural Amp Modeler |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Guitar Amp Software | 8.1 (#7) | 7.4 (#17) |
| Support | Bogren Digital provides a support center with plugin installation and troubleshooting articles and a request submission option. | Builders seeking help can contact [email protected]. |
Plans
In their own words
AmpKnob BDH III
AmpKnob BDH III has no write-up on Specifiction yet; its figures are above.
Neural Amp Modeler
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.