NAM Parametric Plugin v0.4.0

macOS build (universal: arm64 + x86_64) and Windows x64 build. Both are unsigned. macOS: Gatekeeper will block the app/plugin on first launch — see the README for the one-time steps to allow it. Windows: SmartScreen may warn on first run — click 'More info' then 'Run anyway'.

NAM Parametric Plugin v0.3.1-rc1

macOS build (universal: arm64 + x86_64) and Windows x64 build. Both are unsigned. macOS: Gatekeeper will block the app/plugin on first launch — see the README for the one-time steps to allow it. Windows: SmartScreen may warn on first run — click 'More info' then 'Run anyway'.

NAM Parametric Plugin v0.3.1

macOS build (universal: arm64 + x86_64) and Windows x64 build. Both are unsigned. macOS: Gatekeeper will block the app/plugin on first launch — see the README for the one-time steps to allow it. Windows: SmartScreen may warn on first run — click 'More info' then 'Run anyway'.

NAM Parametric Plugin v0.3.0

macOS build (universal: arm64 + x86_64) and Windows x64 build. Both are unsigned. macOS: Gatekeeper will block the app/plugin on first launch — see the README for the one-time steps to allow it. Windows: SmartScreen may warn on first run — click 'More info' then 'Run anyway'.

NAM Parametric Plugin v0.2.0

macOS build (universal: arm64 + x86_64) and Windows x64 build. Both are unsigned. macOS: Gatekeeper will block the app/plugin on first launch — see the README for the one-time steps to allow it. Windows: SmartScreen may warn on first run — click 'More info' then 'Run anyway'.

NAM Parametric Plugin v0.1.0

macOS build (universal: arm64 + x86_64). This build is unsigned/unnotarized — macOS Gatekeeper will block it on first launch. See the README for the one-time steps to allow it to run.

5153 100W (Blue) — Parametric Models v1

Two parametric captures of a 5153 100W (Blue channel) for the NAM Parametric Plugin:

• 5153_100w_Blue_ConcatWaveNet_BoostInput+4dB.nam — ConcatWaveNet architecture (fuller/heavier model).
• 5153_100w_Blue_HyperWaveNet_BoostInput+4dB.nam — HyperWaveNet architecture (lighter/more efficient model).

Prefer the zip below to grab both at once, or download a single .nam file.

⚠️ Input calibration note

These models run a little quiet on the input. Add roughly 4–6 dB of input gain for them to respond like a real 5153.

Future model releases will be more accurately input-calibrated, so this extra input gain won't be needed.

Install

Download a .nam file (or models-5153-v1.zip and unzip it), then load it in the plugin's model loader.