Add MiniMax Music 3

docs/source/en/_toctree.yml

@@ -377,6 +377,8 @@
         title: LuminaNextDiT2DModel
       - local: api/models/minimax_h3_transformer3d
         title: MiniMaxH3Transformer3DModel
+      - local: api/models/minimax_music3_transformer
+        title: MiniMaxMusic3Transformer1DModel
       - local: api/models/mochi_transformer3d
         title: MochiTransformer3DModel
       - local: api/models/motif_video_transformer_3d
@@ -701,6 +703,8 @@
         title: LTX-2
       - local: api/pipelines/ltx_video
         title: LTXVideo
+      - local: api/pipelines/minimax_music3
+        title: MiniMax Music 3
       - local: api/pipelines/minimax_h3
         title: MiniMax-H3
       - local: api/pipelines/mochi

docs/source/en/api/models/minimax_music3_transformer.md

@@ -0,0 +1,22 @@
+<!--Copyright 2026 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+-->
+
+# MiniMaxMusic3Transformer1DModel
+
+The 2.4B flow-matching Diffusion Transformer of [MiniMax Music 3](https://huggingface.co/MiniMaxAI/MiniMax-Music3). It
+denoises 128-channel Flow-VAE audio latents conditioned on the per-frame hidden states of the model's autoregressive
+language-model stage, prepending the flow-matching timestep as an extra sequence token (a Stable-Audio-lineage
+continuous transformer with partial rotary attention and GLU feedforwards).
+
+## MiniMaxMusic3Transformer1DModel
+
+[[autodoc]] MiniMaxMusic3Transformer1DModel

docs/source/en/api/pipelines/minimax_music3.md

@@ -0,0 +1,116 @@
+<!--Copyright 2026 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+-->
+
+# MiniMax Music 3
+
+[MiniMax Music 3](https://huggingface.co/MiniMaxAI/MiniMax-Music3) is a music generation model that produces complete
+songs up to five minutes long from lyrics and a music description, with expressive vocals and long-range structure.
+
+The model is a hybrid of an autoregressive and a diffusion stage: an 8B Qwen3-based global language model predicts one
+semantic audio token per frame while a small depth decoder fills in seven residual RVQ codebooks, and their fused
+hidden states condition a 2.4B flow-matching transformer that produces Flow-VAE latents in overlapping chunks. A
+DAC-style decoder turns the latents into 44.1 kHz stereo audio.
+
+## Usage
+
+MiniMax Music 3 is available as a modular pipeline.
+
+```py
+import soundfile as sf
+import torch
+from diffusers import ModularPipeline
+
+pipe = ModularPipeline.from_pretrained("MiniMaxAI/MiniMax-Music3")
+pipe.load_components(dtype=torch.bfloat16)
+pipe.to("cuda")
+
+lyrics = """[verse]
+Morning light filtering through the pine
+Every quiet street is yours and mine
+[chorus]
+Softly the world begins to breathe"""
+
+prompt = (
+    "Genre: acoustic pop. BPM: 96. Key: C major. Warm and intimate, building gently into the chorus. "
+    "Vocals: soft female lead, close and breathy, light stacked harmonies in the chorus. "
+    "Arrangement: fingerpicked guitar and soft piano; brushed drums and upright bass enter in the chorus."
+)
+
+audio = pipe(
+    prompt=prompt,
+    lyrics=lyrics,
+    audio_duration=60.0,
+    generator=torch.Generator("cuda").manual_seed(7),
+    output="audios",
+)[0]
+
+sf.write("minimax_music3.wav", audio.T, pipe.sampling_rate)
+```
+
+## Reduce memory usage
+
+Refer to the [Reduce memory usage](../../optimization/memory) guide for more details about the various memory saving
+techniques.
+
+The full pipeline needs ~23 GB of VRAM in bfloat16. With automatic CPU offloading a generation runs in ~22 GB of free
+VRAM, and additionally group-offloading the language model fits in 8 GB.
+
+```py
+import torch
+from diffusers import ComponentsManager, ModularPipeline
+from diffusers.hooks.group_offloading import apply_group_offloading
+
+manager = ComponentsManager()
+manager.enable_auto_cpu_offload(device="cuda")
+pipe = ModularPipeline.from_pretrained("MiniMaxAI/MiniMax-Music3", components_manager=manager)
+pipe.load_components(dtype=torch.bfloat16)
+
+# Only needed below ~22 GB of free VRAM — slower, but fits in 8 GB.
+apply_group_offloading(
+    pipe.language_model, onload_device=torch.device("cuda"), offload_type="leaf_level", use_stream=True
+)
+```
+
+## Tips
+
+- Structure tags such as `[intro]`, `[verse]`, `[pre-chorus]`, `[chorus]`, `[bridge]`, `[instrumental]`, `[solo]`, and
+  `[outro]` must each be on their own line in `lyrics`. Text on the same line as a leading tag is dropped by the
+  model's input contract.
+- The music description controls the vocals: describe the vocal gender and timbre explicitly (e.g. "warm female
+  vocal") or the model may drift instrumental. For fine-grained control, structure the description into global
+  metadata (genre, BPM, key, emotional progression), vocal details, and arrangement.
+- `audio_duration` is an upper bound — the language model may end the song earlier with a stop token. The
+  autoregressive stage generates 25 frames per second of audio and dominates the runtime.
+- The classifier-free guidance scale of the flow-matching stage is a guider setting (the reference inference value is
+  1.7): swap it with `pipe.update_components(guider=ClassifierFreeGuidance(guidance_scale=...))`.
+- The pipeline returns the vocoder's native 44.1 kHz stereo output. The reference server additionally resamples to 32
+  kHz; apply your own resampling if you need that exact rate.
+
+## MiniMaxMusic3ModularPipeline
+
+[[autodoc]] MiniMaxMusic3ModularPipeline
+
+## MiniMaxMusic3Blocks
+
+[[autodoc]] MiniMaxMusic3Blocks
+
+## MiniMaxMusic3ConditionEncoder
+
+[[autodoc]] MiniMaxMusic3ConditionEncoder
+
+## MiniMaxMusic3RVQDepthDecoder
+
+[[autodoc]] MiniMaxMusic3RVQDepthDecoder
+
+## MiniMaxMusic3Vocoder
+
+[[autodoc]] MiniMaxMusic3Vocoder