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Neural Amp Modeler

neuralampmodeler.com

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Spec score 7.4 #17 of 35 in Guitar Amp Software

What it is

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.

Spec sheet

What it does
Neural Amp Modeler uses deep learning to create models of guitar amplifiers and pedals with state-of-the-art accuracy.Read 1 Oct 2026 · neuralampmodeler.com
Support
Builders seeking help can contact [email protected].Read 1 Oct 2026 · neuralampmodeler.com
A2 compatibility
Existing A1 models remain supported in NeuralAmpModelerCore and NeuralAmpModelerPlugin.Read 1 Oct 2026 · neuralampmodeler.com
Builder integration
Builders can use NAM's open-source modeling technology in their own products.Read 1 Oct 2026 · neuralampmodeler.com
Gateway plugin
Gateway loads and plays snapshot models of users' favorite gear.Read 1 Oct 2026 · neuralampmodeler.com
Model sharing
Users can share models through TONE3000, a community-organized online library.Read 1 Oct 2026 · neuralampmodeler.com
Model trainer
Users can train models online in Google Colab or install the Python-based trainer locally from PyPI.Read 1 Oct 2026 · neuralampmodeler.com
Open source
NAM has three code repositories available under permissive open-source licenses and open to contributions.Read 1 Oct 2026 · neuralampmodeler.com
Parametric modeling
ParametricOD demonstrates NAM parametric modeling across the full range of an overdrive's knobs and switches.Read 1 Oct 2026 · neuralampmodeler.com
Plugin formats
The plugin repository creates VST3 and AU plugins plus a standalone desktop application.Read 1 Oct 2026 · neuralampmodeler.com
Security notice
NAM's training code depends on PyTorch Lightning, and version 0.12.3 excludes compromised Lightning versions 2.6.2 and 2.6.3.Read 1 Oct 2026 · neuralampmodeler.com
Supported systems
NAM runs on Windows, macOS, Linux, Raspberry Pi, embedded systems, and websites.Read 1 Oct 2026 · neuralampmodeler.com

Plans and prices

Neural Amp Modeler Free open-source project · continuous development Read 1 Oct 2026 · neuralampmodeler.com

Every Neural Amp Modeler plan and price →

Strong points and limits

Strong points

  • Free project with three permissively licensed code repositories.
  • Models can be trained in Google Colab or locally from PyPI.
  • Plugin repository creates VST3 and AU formats.
  • Existing A1 models remain supported.

Limits

  • The training code depends on PyTorch Lightning.
  • Version 0.12.3 excludes Lightning versions 2.6.2 and 2.6.3.

Who it suits

NAM suits guitarists interested in amplifier and pedal models, as well as builders who want to use its open-source modeling technology in their own products. Its training options include a hosted notebook and a locally installed Python trainer.

Verdict

NAM provides model training, playback plugins, and model sharing alongside code that builders can incorporate into products. Check the training dependency version when setting up its training code.

Where Specifiction places it

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