audio-cpp/Magenta-RealTime-2-GGUF

Magenta RealTime 2 — GGUF

Follow or star audio.cpp for runtime updates and new model support.

GGUF conversions of Google DeepMind's Magenta RealTime 2 Small (230M) and Base (2.4B). Generate 48 kHz stereo instrumental music from text or audio style conditioning, with optional note and drum control. Both variants support offline and streaming generation through audio.cpp.

Upstream weights are pinned to google/magenta-realtime-2@010aa0d. The port follows magenta/magenta-realtime@694a545.

File	Generator matrices	Size
magenta-rt2-small-f16.gguf	F16	1.42 GiB
magenta-rt2-small-q8_0.gguf	Q8_0	1.24 GiB
magenta-rt2-base-f16.gguf	F16	5.48 GiB
magenta-rt2-base-q8_0.gguf	Q8_0	3.41 GiB

Download one GGUF. Each package includes the generator, SpectroStream codec, MusicCoCa text/audio style encoder, mapper, quantizer, vocabulary, configuration, and model spec. No external resources or Python runtime are needed for inference. Q8_0 quantizes supported generator matrices; other matrices use F16 where needed. Codec, MusicCoCa, normalization, bias, scale, and sink tensors remain F32.

Quick start

hf download audio-cpp/Magenta-RealTime-2-GGUF \
  magenta-rt2-small-f16.gguf \
  --local-dir Magenta-RealTime-2-GGUF

audiocpp_cli --model Magenta-RealTime-2-GGUF/magenta-rt2-small-f16.gguf \
  --family magenta_realtime_2 --task gen --backend cuda \
  --text "disco funk" --request-option duration_sec=10 \
  --out music.wav --log

For Base, download and select magenta-rt2-base-f16.gguf instead, or choose either -q8_0.gguf package. Use --backend vulkan or --backend cpu for another backend. Add --mode streaming to emit audio in blocks of up to 160 ms while generation continues. Offline and streaming use the same generation path and produce the same final waveform.

Replace the text prompt with --audio style.wav to condition on an audio example. This transfers musical style; it does not continue the input recording.

Request option	Default	Meaning
duration_sec	10	Output duration, rounded up to 40 ms frames.
seed	0	Generation seed.
temperature	1.3	Sampling temperature; 0 is greedy.
top_k	40	Candidate limit; 0 keeps all 1024 valid codes.
guidance_scale	3	Style guidance, -1–7.
note_guidance_scale	1	Note guidance, -1–7.
drum_guidance_scale	1	Drum guidance, -1–7.
use_mapper	true	Map text style into audio embedding space.
drums	-1	Unspecified (-1), no drums (0), or drums (1).
pianoroll_file	unset	JSON array of 128 pitch states per 25 Hz frame.

Set controls through --request-option name=value. See the model guide for pitch-state values and session options. Each request starts fresh music.

Performance

RTX 5090, CUDA, eight host threads, one persistent session per model. After a two-second warmup, generate three different 30-second styles and repeat the first style. Both implementations use temperature 1.3, top-k 40, style guidance 3, note/drum guidance 1, the text mapper enabled, and seed 0.

Warm RTF averages the four measured requests, including style conditioning and waveform generation. RTF is wall time divided by audio duration. Peak VRAM includes model preparation and generation. Python uses its official generate() path; every row measures complete waveform generation.

Model	Runtime	Mode	RTF	Peak VRAM (MiB)
Small	Official Python	Official generation	0.1359	24,626
Small	audio.cpp F16	Offline	0.0861	2,146
Small	audio.cpp F16	Streaming	0.0874	2,146
Small	audio.cpp Q8_0	Offline	0.0833	1,954
Small	audio.cpp Q8_0	Streaming	0.0831	1,954
Base	Official Python	Official generation	0.3714	16,946
Base	audio.cpp F16	Offline	0.2376	6,336
Base	audio.cpp F16	Streaming	0.2335	6,336
Base	audio.cpp Q8_0	Offline	0.1789	4,218
Base	audio.cpp Q8_0	Streaming	0.1789	4,218

Streaming time to first audio

Under the same CUDA settings, TTFA includes text conditioning through the first 160 ms audio block and excludes model loading and preparation. Warm averages cover the four requests after warmup.

Model	First request TTFA	Warm average TTFA
Small F16	218 ms	22.1 ms
Small Q8_0	242 ms	21.4 ms
Base F16	262 ms	46.9 ms
Base Q8_0	267 ms	38.4 ms

Examples

Small F16 — “A gentle acoustic guitar with warm piano”:

Base F16 — “A gentle acoustic guitar with warm piano”:

License

Original model and resources: Copyright 2026 Google LLC, CC-BY-4.0. These are converted weights; the upstream attribution, license, and usage terms continue to apply. audio.cpp inference code is Apache-2.0.