diff --git a/README.md b/README.md
index 3b70d35..cd5f1ad 100644
--- a/README.md
+++ b/README.md
@@ -9,20 +9,13 @@ To get the intended behavior, **you must run your audio host at the same sample
 
 For amp-only models (the most typical), **you will need to run an impulse reponse after this plugin** to model the cabinet.
 
-## Models Supported
+## Models Supported and Performance
 
-The plugin supports both [Neural Amp Modeler (NAM)](https://github.com/sdatkinson/neural-amp-modeler) models and [RTNeural keras json models](https://github.com/jatinchowdhury18/RTNeural) (like those used by [Aida-X](https://github.com/AidaDSP/AIDA-X)).
+The plugin supports both [Neural Amp Modeler (NAM)](https://github.com/sdatkinson/neural-amp-modeler) models (both A1 and A2) and [RTNeural keras json models](https://github.com/jatinchowdhury18/RTNeural) (like those used by [Aida-X](https://github.com/AidaDSP/AIDA-X)).
 
 The best source of models is [Tone3000](https://www.tone3000.com/).
 
-For more information on model type support, see the [NeuralAudio](https://github.com/mikeoliphant/NeuralAudio) repository, which is where the model handling code lives.
-
-## Performance
-
-NAM WaveNet models are generally quite expensive to run. This isn't (much of) an issue on modern PCs, but you may have trouble running on less powerful hardware.
-
-If you are having trouble running a "standard" model, try looking for "feather", or even "nano" (the least expensive) models. You can find a list of ["feather"-tagged models on Tone3000](https://www.tone3000.com/search?sizes=feather). Note that tagging models is up to the submitter, so not all "feather" models are tagged as such - you should be able to find more if you dig around.
-
+For more information on model type support and performance, see the [NeuralAudio](https://github.com/mikeoliphant/NeuralAudio) repository, which is where the model handling code lives.
 
 ## Input Calibration