diff --git a/recipes/README.md b/recipes/README.md
index 4da489c59..67d481860 100644
--- a/recipes/README.md
+++ b/recipes/README.md
@@ -58,6 +58,7 @@ recipes/
 | [`Qwen/Qwen3-Omni.md`](./Qwen/Qwen3-Omni.md) | Online serving for multimodal chat | 1x A100 80GB |
 | [`Qwen/Qwen3-TTS.md`](./Qwen/Qwen3-TTS.md) | Text-to-speech serving (CustomVoice / VoiceDesign / Base) | 1x H100/A100 80GB |
 | [`SenseNova/SenseNova-U1.md`](./SenseNova/SenseNova-U1.md) | Unified image generation and understanding | 1x H200 (144GB) |
+| [`StabilityAI/Stable-Audio-Open.md`](./StabilityAI/Stable-Audio-Open.md) | Offline + online text-to-audio generation (Stable Audio Open) | 1x RTX 4090 24GB |
 | [`Tencent/Covo-Audio-Chat.md`](./Tencent/Covo-Audio-Chat.md) | Online serving for audio chat | 1x A100 80GB |
 | [`Tencent/HunyuanImage-3.0-Instruct.md`](./Tencent/HunyuanImage-3.0-Instruct.md) | DiT-only text-to-image serving and benchmark, including ModelOpt mixed FP8/NVFP4 | 4x H100/H800 80GB / 2x B200 |
 | [`Wan-AI/Wan2.2-I2V.md`](./Wan-AI/Wan2.2-I2V.md) | Image-to-video serving (Wan2.2 14B) | 8x Ascend NPU (A2/A3) |
diff --git a/recipes/StabilityAI/Stable-Audio-Open.md b/recipes/StabilityAI/Stable-Audio-Open.md
new file mode 100644
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+# Stable-Audio-Open Text-To-Audio Generation on 1x GPU
+
+> Text-to-audio recipe for Stable Audio Open with offline inference and
+> OpenAI-compatible online serving on 1x RTX 4090 24GB.
+
+## Summary
+
+- Vendor: Stability AI
+- Model: `stabilityai/stable-audio-open-1.0`
+- Task: Text-to-audio generation
+- Mode: Offline inference and online serving
+- Maintainer: Community
+
+## When to use this recipe
+
+Use this recipe when you want to run Stable Audio Open on a single RTX 4090
+24GB GPU for music or sound-effect generation. The recipe covers a 10-second
+offline validation sample with TeaCache and online serving through the
+`/v1/audio/generate` endpoint.
+
+## References
+
+- Model: <https://huggingface.co/stabilityai/stable-audio-open-1.0>
+- Offline example:
+  [`examples/offline_inference/text_to_audio`](../../examples/offline_inference/text_to_audio)
+- Online example:
+  [`examples/online_serving/stable_audio`](../../examples/online_serving/stable_audio)
+- Audio generation API:
+  [`docs/serving/audio_generate_api.md`](../../docs/serving/audio_generate_api.md)
+- Related issue:
+  [#2645](https://github.com/vllm-project/vllm-omni/issues/2645)
+
+## Hardware Support
+
+### GPU
+
+#### 1x RTX 4090 24GB
+
+##### Environment
+
+- OS: Ubuntu 22.04.5
+- Python: 3.12
+- GPU: NVIDIA GeForce RTX 4090, 24564 MiB VRAM
+- Driver / runtime: NVIDIA driver 595.80, CUDA-capable runtime matching the
+  repository build
+- vLLM version: 0.22.0
+- vLLM-Omni version: source checkout
+- PyTorch: 2.11.0+cu130
+- Model path used in the commands below: `/path/to/stable-audio-open-1.0`
+
+Stable Audio Open is a gated Hugging Face model. Accept the model license on
+the Hugging Face model card before downloading the checkpoint.
+
+```bash
+hf auth login
+
+hf download stabilityai/stable-audio-open-1.0 \
+  --local-dir /path/to/stable-audio-open-1.0
+```
+
+##### Commands
+
+Run a 10-second offline validation sample from the repository root:
+
+```bash
+python examples/offline_inference/text_to_audio/text_to_audio.py \
+  --model /path/to/stable-audio-open-1.0 \
+  --prompt "A gentle piano melody with soft room ambience" \
+  --negative-prompt "Low quality, distorted, noisy" \
+  --seed 42 \
+  --guidance-scale 7.0 \
+  --audio-length 10.0 \
+  --num-inference-steps 50 \
+  --cache-backend tea_cache \
+  --output examples/offline_inference/text_to_audio/stable_audio_10s.wav
+```
+
+Start the online serving endpoint:
+
+```bash
+vllm-omni serve /path/to/stable-audio-open-1.0 \
+  --host 0.0.0.0 \
+  --port 8091 \
+  --gpu-memory-utilization 0.9 \
+  --trust-remote-code \
+  --enforce-eager \
+  --omni
+```
+
+Generate a 10-second WAV file from the repository root in another terminal:
+
+```bash
+curl http://localhost:8091/health
+
+curl -X POST http://localhost:8091/v1/audio/generate \
+  -H "Content-Type: application/json" \
+  -d '{
+    "input": "A gentle piano melody with soft room ambience",
+    "audio_length": 10.0,
+    "num_inference_steps": 50,
+    "guidance_scale": 7.0,
+    "negative_prompt": "Low quality, distorted, noisy",
+    "seed": 42,
+    "response_format": "wav"
+  }' \
+  --output examples/online_serving/stable_audio/piano_10s.wav
+```
+
+##### Verification
+
+Check that:
+
+- The offline command writes a valid WAV file.
+- The server responds on `http://localhost:8091/health`.
+- The online request writes a valid WAV file.
+- The generated audio sample rate is 44.1 kHz.
+- The generated duration is approximately 10 seconds.
+- Peak sampled GPU memory is within the 24GB RTX 4090 budget. In the validated
+  run, offline and online generation each peaked at about 12.6 GiB.
+
+Validate the offline outputs:
+
+```bash
+ls -lh examples/offline_inference/text_to_audio/stable_audio_10s.wav
+
+python - <<'PY'
+import soundfile as sf
+
+path = "examples/offline_inference/text_to_audio/stable_audio_10s.wav"
+audio, sample_rate = sf.read(path)
+print("sample_rate:", sample_rate)
+print("shape:", audio.shape)
+print("duration:", len(audio) / sample_rate)
+PY
+```
+
+Validate the online output:
+
+```bash
+ls -lh examples/online_serving/stable_audio/piano_10s.wav
+
+python - <<'PY'
+import soundfile as sf
+
+path = "examples/online_serving/stable_audio/piano_10s.wav"
+audio, sample_rate = sf.read(path)
+print("sample_rate:", sample_rate)
+print("shape:", audio.shape)
+print("duration:", len(audio) / sample_rate)
+PY
+```
+
+##### Notes
+
+- `stable-audio-open-1.0` can generate up to about 47 seconds of 44.1 kHz
+  stereo audio. This recipe validates 10-second WAV outputs.
+- `--cache-backend tea_cache` is supported and was used for the 10-second
+  offline validation command.
+- The model is gated on Hugging Face and requires license acceptance before
+  download.
+- If online serving fails while importing `torchaudio`, make sure the
+  `torchaudio` wheel matches the installed PyTorch and CUDA build. The
+  validated environment used `torch==2.11.0+cu130` and
+  `torchaudio==2.11.0+cu130`.
+- The `NIXL is not available`, `GLOO_SOCKET_IFNAME`, and `torchsde` boundary
+  warnings observed during validation did not prevent successful generation.
+- This recipe was validated on one RTX 4090 24GB GPU only. Other GPU counts,
+  ROCm, XPU, and NPU setups are not covered here.
+- Long generations, higher inference-step counts, and non-WAV response formats
+  were not benchmarked in this recipe.