Qwen-Audio-3.1-ASR-Flash-Message is a generative speech recognition model optimized for voice messages, voice input, and enterprise scenarios. It supports Chinese, English, and other languages, with optimizations for Indonesian, Japanese, Thai, Filipino, Vietnamese, Korean, and Malay. The model supports incremental streaming transcription, P0/P1 hotwords, text normalization, recognition informed by preceding transcripts and business context, and optional native text polishing. It improves recognition stability with multiple speakers, background conversations, far-field audio, and environmental noise. It supports automatic language detection or specified target languages, and can transcribe Chinese dialects as spoken or convert them to standard Mandarin text.
Inference Service Provider
The inference service provider for qwen-audio-3.1-asr-flash-message is Alibaba Cloud Model Studio.
Model Capabilities
| Capability | Support | Capability | Support |
|---|
| Input Modality | Audio | Output Modality | Text |
| Model Experience | Unsupported | Function Calling | Unsupported |
| Structured Outputs | Supported | Web Search | Unsupported |
| Prefix Completion | Unsupported | Context Caching | Unsupported |
| Batch Inference | Unsupported | Fine-tuning | Unsupported |
Context Limits
| Parameter | Value | Parameter | Value |
|---|
| Max Input Length | 7168 Token | Max Output Length | 1024 Token |
| Context Window | 8192 Token | | |
Pricing
This page only shows the original pricing for model API calls, excluding any limited-time promotions. Visit Model Studio Console for promotional offers.
China (Beijing)
| Billing item | Price (USD) | Unit |
|---|
| Input | 0.848 | Per million tokens |
| Output | 0.636 | Per million tokens |
Singapore
Scope: International
| Billing item | Price (USD) | Unit |
|---|
| Input | 0.93 | Per million tokens |
| Output | 0.70 | Per million tokens |
Rate Limits
China (Beijing)
| Parameter | Value |
|---|
| RPM (requests per minute) | 1200 |
Singapore
Scope: International
| Parameter | Value |
|---|
| RPM (requests per minute) | 1200 |
API usage