| --- |
| license: apache-2.0 |
| pipeline_tag: audio-text-to-text |
| library_name: transformers |
| tags: |
| - audio-reasoning |
| - chain-of-thought |
| - multi-modal |
| - step-audio-r1 |
| --- |
| |
| ## Overview of Step-Audio-R1.1 |
|
|
| <a href="https://www.stepfun.com/studio/audio?tab=conversation"><img src="https://img.shields.io/static/v1?label=Space%20Playground&message=Studio&color=yellow"></a> <a href="https://huggingface.co/spaces/stepfun-ai/Step-Audio-R1"><img src="https://img.shields.io/static/v1?label=Space&message=Web&color=green"></a>   |
|
|
| ### Introduction |
| Step-Audio R1.1 (Realtime) is a major upgrade to Step-Audio-R1, designed for interactive spoken dialogue with both **real-time responsiveness** and **strong reasoning capability**. |
|
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| Unlike conventional streaming speech models that trade intelligence for latency, R1.1 enables *thinking while speaking*, achieving high intelligence without sacrificing speed. |
|
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| ### Mind-Paced Speaking (Low Latency) |
| Based on the research [*Mind-Paced Speaking*](MPS.pdf), the Realtime variant adopts a **Dual-Brain Architecture**: |
| - A **Formulation Brain** responsible for high-level reasoning |
| - An **Articulation Brain** dedicated to speech generation |
|
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| This decoupling allows the model to perform **Chain-of-Thought reasoning during speech output**, maintaining ultra-low latency while handling complex tasks in real time. |
|
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| ### Acoustic-Grounded Reasoning (High Intelligence) |
| To address the *inverted scaling* issue鈥攚here reasoning over transcripts can degrade performance鈥擲tep-Audio R1.1 grounds its reasoning directly in acoustic representations rather than text alone. |
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| Through iterative self-distillation, extended deliberation becomes a strength instead of a liability. This enables effective test-time compute scaling and leads to **state-of-the-art performance**, including top-ranking results on the AA benchmark. |
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| ## Online demonstration |
|
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| ### StepFun Audio Studio |
|
|
| - Both Step-Audio-R1.1 are available in our [StepFun Audio Studio](https://www.stepfun.com/studio/audio). |
| - You will need an API key from the [StepFun Open Platform](https://platform.stepfun.com/). |
|
|
| ## WeChat group |
|
|
| You can scan the following QR code to join our WeChat group for communication and discussion. |
| <div align="center"> |
| <img src="https://huggingface.co/proxy/cdn-uploads.huggingface.co/production/uploads/66518fd07d8cb2629a514c18/DRdnp1SN-yxhlNOfy26mE.jpeg" width="200" alt="QR code"> |
| </div> |
|
|
| ## Model Usage |
| ### 馃摐 Requirements |
| - **GPU**: NVIDIA GPUs with CUDA support (tested on 4脳L40S/H100/H800/H20). |
| - **Operating System**: Linux. |
| - **Python**: >= 3.10.0. |
|
|
| ### 猬囷笍 Download Model |
| First, you need to download the Step-Audio-R1 model weights. |
|
|
| **Method A 路 Git LFS** |
| ```bash |
| git lfs install |
| git clone https://huggingface.co/stepfun-ai/Step-Audio-R1.1 |
| ``` |
|
|
| **Method B 路 Hugging Face CLI** |
| ```bash |
| hf download stepfun-ai/Step-Audio-R1.1 --local-dir ./Step-Audio-R1.1 |
| ``` |
|
|
| ### 馃殌 Deployment and Execution |
| We provide two ways to serve the model: Docker (recommended) or compiling the customized vLLM backend. |
|
|
| #### 馃惓 Method 1 路 Run with Docker (Recommended) |
|
|
| A customized vLLM image is required. |
|
|
| 1. **Pull the image**: |
| ```bash |
| docker pull stepfun2025/vllm:step-audio-2-v20250909 |
| ``` |
| 2. **Start the service**: |
| Assuming the model is downloaded in the `Step-Audio-R1` folder in the current directory. |
| |
| ```bash |
| docker run --rm -ti --gpus all \ |
| -v $(pwd)/Step-Audio-R1.1:/Step-Audio-R1.1 \ |
| -p 9999:9999 \ |
| stepfun2025/vllm:step-audio-2-v20250909 \ |
| -- vllm serve /Step-Audio-R1.1 \ |
| --served-model-name Step-Audio-R1.1 \ |
| --port 9999 \ |
| --max-model-len 16384 \ |
| --max-num-seqs 32 \ |
| --tensor-parallel-size 4 \ |
| --chat-template '{%- macro render_content(content) -%}{%- if content is string -%}{{- content.replace("<audio_patch>\n", "<audio_patch>") -}}{%- elif content is mapping -%}{{- content['"'"'value'"'"'] if '"'"'value'"'"' in content else content['"'"'text'"'"'] -}}{%- elif content is iterable -%}{%- for item in content -%}{%- if item.type == '"'"'text'"'"' -%}{{- item['"'"'value'"'"'] if '"'"'value'"'"' in item else item['"'"'text'"'"'] -}}{%- elif item.type == '"'"'audio'"'"' -%}<audio_patch>{%- endif -%}{%- endfor -%}{%- endif -%}{%- endmacro -%}{%- if tools -%}{{- '"'"'<|BOT|>system\n'"'"' -}}{%- if messages[0]['"'"'role'"'"'] == '"'"'system'"'"' -%}{{- render_content(messages[0]['"'"'content'"'"']) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{{- '"'"'<|BOT|>tool_json_schemas\n'"'"' + tools|tojson + '"'"'<|EOT|>'"'"' -}}{%- else -%}{%- if messages[0]['"'"'role'"'"'] == '"'"'system'"'"' -%}{{- '"'"'<|BOT|>system\n'"'"' + render_content(messages[0]['"'"'content'"'"']) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- endif -%}{%- for message in messages -%}{%- if message["role"] == "user" -%}{{- '"'"'<|BOT|>human\n'"'"' + render_content(message["content"]) + '"'"'<|EOT|>'"'"' -}}{%- elif message["role"] == "assistant" -%}{{- '"'"'<|BOT|>assistant\n'"'"' + (render_content(message["content"]) if message["content"] else '"'"''"'"') -}}{%- set is_last_assistant = true -%}{%- for m in messages[loop.index:] -%}{%- if m["role"] == "assistant" -%}{%- set is_last_assistant = false -%}{%- endif -%}{%- endfor -%}{%- if not is_last_assistant -%}{{- '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- elif message["role"] == "function_output" -%}{%- else -%}{%- if not (loop.first and message["role"] == "system") -%}{{- '"'"'<|BOT|>'"'"' + message["role"] + '"'"'\n'"'"' + render_content(message["content"]) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%}{{- '"'"'<|BOT|>assistant\n<think>\n'"'"' -}}{%- endif -%}' \ |
| --enable-log-requests \ |
| --interleave-mm-strings \ |
| --trust-remote-code |
| ``` |
| After the service starts, it will listen on `localhost:9999`. |
| |
| #### 馃惓 Method 2 路 Run from Source (Compile vLLM) |
| Step-Audio-R1 requires a customized vLLM backend. |
|
|
| 1. **Download Source Code**: |
| ```bash |
| git clone https://github.com/stepfun-ai/vllm.git |
| cd vllm |
| ``` |
| |
| 2. **Prepare Environment**: |
| ```bash |
| python3 -m venv .venv |
| source .venv/bin/activate |
| ``` |
| |
| 3. **Install and Compile**: |
| vLLM contains both C++ and Python code. We mainly modified the Python code, so the C++ part can use the pre-compiled version to speed up the process. |
| |
| ```bash |
| # Use pre-compiled C++ extensions (Recommended) |
| VLLM_USE_PRECOMPILED=1 pip install -e . |
| ``` |
| |
| 4. **Switch Branch**: |
| After compilation, switch to the branch that supports Step-Audio. |
| ```bash |
| git checkout feat/step-audio-support |
| ``` |
| |
| 5. **Start the Service**: |
| ```bash |
| # Ensure you are in the vllm directory and the virtual environment is activated |
| source .venv/bin/activate |
| |
| python3 -m vllm.entrypoints.openai.api_server \ |
| --model ../Step-Audio-R1.1 \ |
| --served-model-name Step-Audio-R1.1 \ |
| --port 9999 \ |
| --host 0.0.0.0 \ |
| --max-model-len 65536 \ |
| --max-num-seqs 128 \ |
| --tensor-parallel-size 4 \ |
| --gpu-memory-utilization 0.85 \ |
| --trust-remote-code \ |
| --enable-log-requests \ |
| --interleave-mm-strings \ |
| --chat-template '{%- macro render_content(content) -%}{%- if content is string -%}{{- content.replace("<audio_patch>\n", "<audio_patch>") -}}{%- elif content is mapping -%}{{- content['"'"'value'"'"'] if '"'"'value'"'"' in content else content['"'"'text'"'"'] -}}{%- elif content is iterable -%}{%- for item in content -%}{%- if item.type == '"'"'text'"'"' -%}{{- item['"'"'value'"'"'] if '"'"'value'"'"' in item else item['"'"'text'"'"'] -}}{%- elif item.type == '"'"'audio'"'"' -%}<audio_patch>{%- endif -%}{%- endfor -%}{%- endif -%}{%- endmacro -%}{%- if tools -%}{{- '"'"'<|BOT|>system\n'"'"' -}}{%- if messages[0]['"'"'role'"'"'] == '"'"'system'"'"' -%}{{- render_content(messages[0]['"'"'content'"'"']) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{{- '"'"'<|BOT|>tool_json_schemas\n'"'"' + tools|tojson + '"'"'<|EOT|>'"'"' -}}{%- else -%}{%- if messages[0]['"'"'role'"'"'] == '"'"'system'"'"' -%}{{- '"'"'<|BOT|>system\n'"'"' + render_content(messages[0]['"'"'content'"'"']) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- endif -%}{%- for message in messages -%}{%- if message["role"] == "user" -%}{{- '"'"'<|BOT|>human\n'"'"' + render_content(message["content"]) + '"'"'<|EOT|>'"'"' -}}{%- elif message["role"] == "assistant" -%}{{- '"'"'<|BOT|>assistant\n'"'"' + (render_content(message["content"]) if message["content"] else '"'"''"'"') -}}{%- set is_last_assistant = true -%}{%- for m in messages[loop.index:] -%}{%- if m["role"] == "assistant" -%}{%- set is_last_assistant = false -%}{%- endif -%}{%- endfor -%}{%- if not is_last_assistant -%}{{- '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- elif message["role"] == "function_output" -%}{%- else -%}{%- if not (loop.first and message["role"] == "system") -%}{{- '"'"'<|BOT|>'"'"' + message["role"] + '"'"'\n'"'"' + render_content(message["content"]) + '"'"'<|EOT|>'"'"' -}}{%- endif -%}{%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%}{{- '"'"'<|BOT|>assistant\n<think>\n'"'"' -}}{%- endif -%}' |
| ``` |
| |
| After the service starts, it will listen on `localhost:9999`. |
