ToneCast LogoTONECAST
Windows Standalone + VST3 · In Development

Every tone.
One player.

A modern NAM model and cabinet IR player for Windows. Load your favorite captures, shape your signal, save presets, and play through a standalone application or directly inside your DAW.

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IconTONECAST PLAYER
01. INPUT / GATE
Input Gain+2.4 dB
Noise Gate-65 dB
IN: -12.4dBGATE: CLOSED
02. DSP ENGINE
96 kHz64 Spls
NAM AMPLoaded Model

Plexi-1959-SuperLead-Bright.nam

Gain Match: Active · Capture Res: Standard
CAB IRCabinet Impulse Response

Greenback-4x12-SM57-Edge.wav

Length: 200ms · Phase-Aligned · Stereo
03. OUTPUT
Output Gain-1.5 dB
BypassENGAGED
OUT: -13.9dBLATENCY: 0ms
Live Signal Path

Interactive Signal Chain

Visualize and preview how your guitar signal travels through ToneCast. Drag controls below to adjust settings in real-time.

SIGNAL ROUTING ENGINE
STEP 01 // INPUT

Input Stage

Gain staging before the digital converters.

Gain+2.4 dB
STEP 02 // DYNAMICS

Noise Gate

Removes hum and guitar noise during silences.

Thresh-65 dB
STEP 03 // CORE DSP

NAM Amplifier

High-precision neural-net amplifier simulation.

Select Model:
STEP 04 // SPACE

Cabinet IR

Simulates speaker cabinet acoustic spaces.

Select Cab IR:
STEP 05 // OUTPUT

Output Stage

Final volume trim stage before signal export.

Output-1.5 dB
STATUS:Amplifying through Plexi 1959 Super Lead and cabinet Greenback 4x12 SM57
LATENCY: 0.0ms (Real-time)CPU: 1.4%
Core Engine Capabilities

Built for Serious Playing

Explore what ToneCast delivers for Windows standalone players and plugin wrappers today, tomorrow, and in the future.

Available

Load NAM Models

Import local .nam files and organize your preferred neural amplifier captures in a high-performance library.

Available

Cabinet Impulse Responses

Load compatible zero-latency .wav cabinet IRs and pair them with your favorite amp captures.

Available

Standalone Performance

Connect your audio interface, configure low-latency ASIO drivers, and play directly without opening a DAW.

Available

VST3 Workflow

Load ToneCast directly inside Cubase, Reaper, Ableton Live, FL Studio, and other compatible Windows DAWs.

Available

Preset Management

Save and recall complete rigs instantly: amp models, cabinet IRs, gate thresholds, and fine gain staging.

Available

Local-First Workflow

Keep your amp models, IRs, and presets fully local. No login, no cloud subscription, and no internet required.

In Development

TONE3000 Integration

Browse, search, and download compatible captures directly from the TONE3000 cloud within the standalone app.

In Development

Advanced Library Management

Filter, tag, and favorite your growing capture collection for instant access during sessions.

Planned

Mobile Companion App

A mobile companion experience for reviewing, searching, and managing your rig presets on the go.

Application Tour

Explore the Interface

Inspect the visual elements of ToneCast. Select a view below to preview the responsive layout designs.

MAIN PLAYER VIEW
INPUT
GATE
OUTPUT
MIX
LOADED: Plexi-Lead-Amp-1959.nam
Windows stand-alone v1.0.0-devLocal-First DSP Engine
Target Comparison

Standalone vs VST3 Plugin

A clear look at how features map between the standalone application and the DAW plugin formats.

FeatureWindows StandaloneVST3 Plugin
Load local NAM models Yes Yes
Load cabinet WAV IRs Yes Yes
Save & Load rig presets Yes Yes
ASIO device selection YesControlled by DAW host
TONE3000 online browsing PlannedNot Planned
Offline local playback Yes Yes

Note: Standing features verified against target core DSP engine specifications in the local application project.

Guitarist Workflows

Fits Your Playing Setup

Whether you are tweaking tones on headphones at 2 AM or tracking a final solo in your DAW, ToneCast handles it.

PHASE 01

Practice

Launch the standalone ToneCast app, select your ASIO audio interface, load your favorite profile, and start playing in seconds without ever opening a DAW project.

PHASE 02

Record

Load ToneCast as a low-overhead VST3 audio plugin on your track, record clean DI tracks, and adjust your amp models or cabinet profiles with complete session recall.

PHASE 03

Explore

Organize your collection of NAM files locally. Once launched, TONE3000 integrations will allow you to browse and test new captures directly in your signal flow.

TONE3000 BROWSER CONCEPTPLANNED
MARSHALL PLEXI 1959Plexi_SuperLead_Bright_M57.nam
PREVIEW
SOLDANO SLO-100SLO_Classic_Lead_Active.nam
VOX AC30 CHASSISAC30_TopBoost_Blue.nam
PREVIEW
Ecosystem Expansion

Discover your next tone.

Browse, search, and download compatible captures from TONE3000 directly within the ToneCast standalone application, without ever opening a web browser.

Architecture Restriction

TONE3000 integration is planned strictly for the standalone player application. Online browsing and cloud operations will not run inside the VST3 plugin container to ensure complete DSP session stability and security.

Real-time Performance

Built for responsive playing.

ToneCast is being developed around the open-source Neural Amp Modeler (NAM) ecosystem, with a deep focus on low-latency operation, predictable CPU resource usage, and dependable DAW session recall.

By splitting the user interface rendering thread from the real-time audio processing core, ToneCast prevents GUI redraw operations from causing audio dropouts or buffer clicks, even when running at small ASIO buffer sizes.

DSP ArchitectureThread-Safe DSP Orchestration

Isolated signal paths for parameter settings and audio inference block execution.

State LoadingDependable Preset Recalls

Every loaded model, cabinet impulse WAV, gain level, and gate state saves cleanly inside your DAW session.

Project Roadmap

Development Timeline

A transparent look at the planned feature development phases for the ToneCast player project.

NOW

In Active Development
  • Windows Standalone AppCore player with low-latency ASIO support.
  • VST3 DAW PluginCompatible with major Windows DAWs.
  • Local NAM LoadingLoad neural captures (.nam files) directly.
  • Cabinet IR LoadingLoad speaker cabinet responses (.wav files).
  • Zero-Latency DSP CoreUltra-fast inference based on upstream NAM core.
  • Signal ControlsInput/Output gain staging & Noise Gate threshold.
  • Rig PresetsSave and load full hardware snapshots locally.

NEXT

Short-Term Roadmap
  • TONE3000 Library BrowserSearch and load online models directly within the standalone app.
  • Advanced Metadata LoaderParse amp model files to show capture parameters (e.g., gain levels).
  • Favorites & TagsOrganize and search local rigs easily.
  • Preset SharingExport and import ToneCast preset files.
  • Automatic Update CheckerStay updated with new builds automatically.

LATER

Future Goals
  • Additional Plugin FormatsInvestigation of CLAP and AAX formats.
  • Mobile Companion ExperienceRig preset editor and model search for Android and iOS.
  • macOS Platform ResearchCore engine porting and AU/VST3 target support.
  • Expanded Community FeaturesCloud syncing and community preset rating system.
Transparency & License

Built in the open.

ToneCast builds upon the Neural Amp Model open-source DSP ecosystem. We believe in open, transparent software that respects musician sovereignty and privacy.

View SourceRead License InfoReport an Issue
Early Access Program

Join the Beta Queue

Sign up below to receive testing build announcements, development updates, and immediate notify notifications when stable installers release.

Knowledge Base

Frequently Asked Questions

Search or filter our catalog of questions to understand the system and core DSP features.

ToneCast is a polished, fast Neural Amp Modeler (NAM) player for Windows. It lets you load and play custom amplifier captures and cabinet impulse responses (IRs) in real time with minimal latency, either as a standalone application or a VST3 plugin.
A Neural Amp Modeler (NAM) model is a highly accurate, machine-learning-based representation of a guitar amplifier or pedal. Created using the open-source Neural Amp Modeler training software, these models capture the real physical dynamics and compression of analog circuits.
No, ToneCast is optimized strictly as a player and loader. It does not train new models. Training models requires intensive GPU computation and is handled separately using the upstream Python neural-amp-modeler project.
ToneCast supports standard .nam files. These models can be loaded directly from your local drive without requiring conversion.
ToneCast supports standard audio .wav impulse response files. You can load 24-bit or 16-bit mono or stereo WAV files at any common sample rate (44.1kHz, 48kHz, 88.2kHz, 96kHz).
Yes! The Windows standalone application includes an integrated audio device manager that supports low-latency ASIO drivers. You can plug in your audio interface, adjust your inputs/outputs, and play guitar directly without launching a DAW.
ToneCast supports the VST3 format on Windows. VST3 is fully compatible with modern DAWs such as Cubase, Reaper, Studio One, Ableton Live, FL Studio, and Bitwig Studio.
Yes. ToneCast is local-first. All core features — loading models, loading cabinet WAVs, presets, and audio signal processing — run completely offline on your computer. An internet connection is only needed for the planned TONE3000 online library browser.
Currently, ToneCast is Windows-first, targeting the Windows standalone application and VST3 format. Investigation for a macOS version is listed on our roadmap under planned long-term items.
Android support is a long-term roadmap goal. The core DSP engine is separated to allow potential integration into mobile app containers in the future.
TONE3000 is an upcoming online library browser integrated directly into the ToneCast standalone application. It will allow you to browse, search, download, and test community-created amp models and IRs directly in your signal chain.
Yes. ToneCast builds on the open-source Neural Amp Modeler ecosystem. The core parts are developed openly, and the source code is hosted on GitHub.
ToneCast is currently in active development. We are running an Early Access program for guitarists, producers, and developers. Register your interest below to receive testing access and updates.
Direct downloads will be available as soon as stable build installers are compiled. For now, you can sign up for early access, or view and build the source code directly from the GitHub repository.