feat: Add docs for audio models

docs/tutorials/audio.md

@@ -0,0 +1,96 @@
+<!--
+SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-License-Identifier: Apache-2.0
+-->
+
+# Profile Audio Language Models with AIPerf
+
+AIPerf supports benchmarking Audio Language Models that process audio inputs with optional text prompts.
+
+This guide covers profiling audio models using OpenAI-compatible chat completions endpoints with vLLM.
+
+---
+
+## Start a vLLM Server
+
+Launch the vLLM server with Qwen2-Audio-7B-Instruct:
+
+<!-- setup-vllm-audio-openai-endpoint-server -->
+```bash
+docker pull vllm/vllm-openai:latest
+docker run --gpus all -p 8000:8000 vllm/vllm-openai:latest \
+  --model Qwen/Qwen2-Audio-7B-Instruct \
+  --trust-remote-code
+```
+<!-- /setup-vllm-audio-openai-endpoint-server -->
+
+
+Verify the server is ready:
+
+<!-- health-check-vllm-audio-openai-endpoint-server -->
+```bash
+curl -s http://localhost:8000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "Qwen/Qwen2-Audio-7B-Instruct",
+    "messages": [{"role": "user", "content": "Hello"}],
+    "max_tokens": 10
+  }' | jq
+```
+<!-- /health-check-vllm-audio-openai-endpoint-server -->
+
+---
+
+## Profile with Synthetic Audio
+
+AIPerf can generate synthetic audio for benchmarking:
+
+<!-- aiperf-run-vllm-audio-openai-endpoint-server -->
+```bash
+aiperf profile \
+    --model Qwen/Qwen2-Audio-7B-Instruct \
+    --endpoint-type chat \
+    --audio-length-mean 5.0 \
+    --audio-format wav \
+    --audio-sample-rates 16 \
+    --streaming \
+    --url localhost:8000 \
+    --request-count 20 \
+    --concurrency 4
+```
+<!-- /aiperf-run-vllm-audio-openai-endpoint-server -->
+
+To add text prompts alongside audio, include `--synthetic-input-tokens-mean 100`
+
+## Profile with Custom Input File
+
+Create a JSONL file with audio data and optional text prompts.
+
+<!-- aiperf-run-vllm-audio-openai-endpoint-server -->
+```bash
+cat <<EOF > inputs.jsonl
+{"texts": ["Transcribe this audio."], "audios": ["wav,UklGRiIFAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0Yf4EAAD..."]}
+{"texts": ["What is being said in this recording?"], "audios": ["mp3,SUQzBAAAAAAAI1RTU0UAAAAPAAADTGF2ZjU4Ljc2LjEwMAAAAAAAAAAA..."]}
+{"texts": ["Summarize the main points from this audio."], "audios": ["wav,UklGRooGAABXQVZFZm10IBAAAAABAAEAgD4AAAB9AAACABAAZGF0YWY..."]}
+EOF
+```
+<!-- /aiperf-run-vllm-audio-openai-endpoint-server -->
+
+The audio data format is: `{format},{base64_encoded_audio_data}` where:
+- `format`: Either `wav` or `mp3`
+- `base64_encoded_audio_data`: Base64-encoded audio file content
+
+Run AIPerf using the custom input file:
+
+<!-- aiperf-run-vllm-audio-openai-endpoint-server -->
+```bash
+aiperf profile \
+    --model Qwen/Qwen2-Audio-7B-Instruct \
+    --endpoint-type chat \
+    --input-file inputs.jsonl \
+    --custom-dataset-type single_turn \
+    --streaming \
+    --url localhost:8000 \
+    --request-count 3
+```
+<!-- /aiperf-run-vllm-audio-openai-endpoint-server -->