HiAPI
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Alibaba

Qwen Audio 3.0 TTS

qwen-audio-3.0-tts-plus

Alibaba Tongyi's managed multilingual speech synthesis series, with two tiers—low-latency Flash and high-quality Plus—supporting natural language instructions to control emotion and expressive style

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Pricing

qwen-audio-3.0-tts-plus per 1,000 characters

Unit Price $0.040

Positioning Overview

Qwen Audio 3.0 TTS Plus is the hosted model in Alibaba's Qwen Audio 3.0 TTS series aimed at high-quality speech generation. It is called through the unified HiAPI.ai interface, and text input is turned into natural, faithful speech output. It supports multilingual synthesis of long text, allows natural-language instructions to guide emotion and expressive style, and offers parameter controls such as speech rate, pitch, volume, sample rate, and output format. It is suited to generative scenarios where audio quality and timbre performance matter more than real-time responsiveness, such as spoken-word content, course narration, customer-service announcements, and multilingual dubbing.

Core Highlights

  • A Plus tier focused on audio quality — compared with the Flash model in the same series, it emphasizes naturalness and timbre fidelity more, making it suitable for offline or batch speech production that does not require strict real-time performance.
  • Instruction-based control of expressive style — synthesis instructions can describe emotion and delivery, reducing rework from segment-by-segment auditioning and post-editing.
  • Up to 20,000 characters of text per synthesis — a single task accepts up to 20,000 Unicode code points, so long documents can be submitted in one piece, reducing segment stitching and boundary handling.
  • Finely tunable output parameters — speech rate, pitch, and volume are all adjustable within ranges, and sample rate and container format are selectable, making it easy to integrate with downstream audio pipelines.

Capability Details

Multilingual speech synthesis: supports synthesis prompts for more than ten languages, so a single integration can generate speech for Chinese, English, Japanese, Korean, and other multilingual content, lowering the cost of integrating multilingual content.

Natural-language instruction-guided style: synthesis instructions describe tone, emotion, and delivery, letting the same text produce different narration styles without changing the voice or post-processing.

Audio parameter control: speech rate, pitch, volume, and output sample rate can be set, and output formats such as mp3, wav, pcm, and opus can be chosen as needed, making it convenient to connect directly to playback or transcoding pipelines.

Deterministic synthesis: a random seed can be set to reproduce consistent synthesis results for the same text, which helps with regression testing and content version management.

Adjustable Opus bitrate: the bitrate can be specified when outputting Opus, balancing audio quality and file size in bandwidth-sensitive distribution scenarios.

Applicable Scenarios

  • Turning manuscripts into speech for spoken-content creators — submit a long article or chapter text once and produce audio that can be published directly on podcast and audiobook platforms, reducing segment synthesis and stitching work.
  • Course-script narration for online education providers — synthesize course scripts into consistently styled instructional audio for courseware voiceover and review audio, shortening the recording cycle.
  • Announcement script generation for customer-service teams — convert standardized script text into audio assets for fixed announcements in call centers and self-service channels.
  • Cross-language dubbing for content teams — use language prompts to generate corresponding speech for multilingual versions of scripts, for localization of product introductions and marketing materials.

Limitations and Selection Advice

The Plus tier prioritizes audio quality over speed and is slower than the Flash model in the same series, so it is not suitable for real-time conversation scenarios that are sensitive to first-packet latency; such needs should prioritize Flash. Currently only two system voices are offered, and designing voices from text descriptions is not supported; voice cloning capability is not available on all channels, so confirm before integration. In addition, it is a hosted synthesis service and does not offer self-hosted deployment; if localized deployment or deep model customization is required, a different choice should be made.

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