NAM A2 Just Changed the Game for Every Guitarist on the Planet
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If you've been paying attention to the amp modeling world (and if you're reading this, you definitely have), you already know that Neural Amp Modeler has been quietly eating everyone's lunch for a while now. Free, open source, and scary accurate. But it had a problem: it was basically chained to your DAW. Running NAM captures on actual hardware? That took serious processing power, which meant serious money.
That just changed in a massive way.
What Is NAM Architecture 2 (A2)?
TONE3000 and NAM creator Steve Atkinson just dropped Architecture 2, and it's not a small update. This is a ground-up rebuild of how Neural Amp Modeler works under the hood. The short version: A2 sounds better than anything before it, uses way less CPU, and runs on a chip that costs three bucks. Yeah, three dollars. That's less than the price of a set of strings.
What does that actually mean for you? It means NAM captures aren't just a DAW thing anymore. Budget multi-effects pedals and combo amps can now run NAM natively. The walls of the walled garden just came down, and your tone gets to roam free.
The Numbers Don't Lie
TONE3000 didn't just claim A2 sounds better. They proved it. They ran head-to-head quantitative tests against Neural DSP's Neural Capture V2, IK Multimedia's ToneX V2, and Line 6's Proxy across 39 different tones covering everything from sparkling Fender cleans to a dimed Mesa Dual Rectifier. A2 beat all of them by a wide margin.
Then they ran a blind listening test with over 1,000 participants and more than 100,000 ratings using the MUSHRA methodology (the same standard the BBC uses to evaluate audio quality). A2-Full scored a perfect 100, tying with the real recorded gear. Let that sink in. In a blind test, people literally could not tell the difference between A2 and the actual amp.
That's not incremental improvement. That's the finish line.
Why This Matters for Your Rig
Here's where it gets really exciting. A2 comes in two sizes:
A2-Full is the maximum-accuracy beast for pro audio and DAW work. It delivers better quality than the original NAM architecture while using 30-40% less CPU. Translation: you can run three A2-Full models for the same CPU cost as two old-school NAM models. If you're using Six String Lab's NAM captures for recording, your sessions just got a lot more flexible.
A2-Lite is the one that changes everything for live players. It runs at 50% CPU on a $3 ARM chip. To put that in perspective, a MacBook with an M-series chip can run 200 A2-Lite models simultaneously. You'll never need that many, but knowing you could is pretty fun.
Hardware Support Is Already Rolling In
This isn't vaporware. Major companies are already onboard. Blackstar, Darkglass, HeadRush, Lava Music, Chaos Audio, and Dimehead are all supporting A2, with dozens more announcing support later this year.
HeadRush confirmed that Prime, Core, and Flex Prime users will be able to load NAM captures directly to their rigs this summer with no lossy conversion. Their touchscreen and Wi-Fi integration will let you browse TONE3000's library right on your pedal. If you've been building a library of HeadRush clones, this opens up a whole new world of tones alongside them.
Blackstar already launched the Beam Mini, the first amp with native NAM support, and they're offering free verified NAM captures of their Artisan Series, St. James 100, and more through TONE3000.
Open Source Means Open Season
The best part? A2 is fully open source. The model architecture, training code, and inference engine are all free to use, modify, and ship in commercial products. No license fees. No walled gardens. No "works only with our hardware" nonsense.
This is huge for the capture ecosystem. NAM files work anywhere NAM is supported, just like IR files or MIDI files. Your NAM captures from Six String Lab will work in the Gateway plugin, on a Blackstar Beam Mini, on a HeadRush Prime, and on whatever hardware comes next. Buy once, play everywhere.
What This Means for the Amp Modeling Landscape
Let's be real for a second. The amp modeling market has been getting more crowded and more competitive every year. Tonex captures are incredible. Kemper profiles still sound fantastic. The NeuralDSP captures on the Quad Cortex are world-class. But all of those platforms keep your tones locked into their ecosystem.
NAM A2 is the first technology that says: your tone belongs to you, not to a hardware company. And it backs that up with sound quality that matches or beats everything else on the market.
Does that mean you should throw out your Kemper or sell your Quad Cortex? Of course not. Those are amazing pieces of gear, and Six String Lab has killer tones for all of them. But it does mean the future is more open than it's ever been, and that's good for everyone who plays guitar.
How to Get Started with A2
Getting up and running with A2 is dead simple:
First, head to TONE3000 and browse their library. There are hundreds of thousands of tones available, all in the latest A2 format. Second, download the Gateway plugin from neuralampmodeler.com. It's free. Third, point the plugin at your downloaded tones and start playing.
And if you want pro-quality, meticulously captured tones that are ready to go right now, check out Six String Lab's NAM capture library. We've been obsessing over NAM tone since day one, and every pack we make is designed to sound incredible through A2.
The Bottom Line
NAM A2 is the most significant thing to happen in amp modeling in years. Better sound quality than anything before it. Runs on hardware that costs less than a coffee. Fully open source. And backed by real companies shipping real products right now.
The capture revolution isn't coming. It's here. And it just got a turbo boost.
Whether you're running NAM captures, Tonex captures, Kemper profiles, HeadRush clones, or NeuralDSP captures, the best time to be a guitarist is right now. Head over to sixstringlab.com and grab some tones. Your amp collection just got infinite.
And hey, if you want to try before you buy, we've got free packs that'll blow your mind. No excuses.