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Qwen-Audio-3.1-ASR

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Overview

Qwen-Audio-3.1-ASR-Flash-Filetrans is an end-to-end offline speech recognition model designed for scenarios such as meeting transcription, content production, and call analysis. It supports multilingual and multi-regional Chinese dialect recognition. The model features high-precision transcription, hot word and context enhancement, speaker separation, punctuation prediction, and text normalization capabilities. It maintains stable performance even in complex noisy environments, making it the preferred choice for long audio transcription. This version also supports controllable ASR/AST output for multiple dialects.

Input

Audio

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Input
    $0.15Per 1M tokens
  • Output
    $0.47Per 1M tokens

Rate Limits

  • RPMRequests Per Minute
    600

API Reference

Call API
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curl --location 'https://maas.qwencloudapi.com/api/v1/services/audio/asr/transcription' \
     --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
     --header "Content-Type: application/json" \
     --header "X-DashScope-Async: enable" \
     --data '{
    "model": "qwen-audio-3.1-asr-flash-filetrans",
    "input": {
        "file_urls": [
            "{YOUR_AUDIO_URL}"
        ]
    },
    "parameters": {
        "channel_id": [0]
    }
}'