Qwen/Qwen3-TTS-VoiceDesign
Qwen3-TTS-VoiceDesign is a voice design variant of Qwen3-TTS by Alibaba's Qwen team. Instead of selecting from preset voices, you describe the voice you want in natural language — and the model generates speech in that voice. Key capabilities: - Natural language voice control — describe any voice with free text (e.g. "a deep male voice with a calm, authoritative presence", "a young cheerful female with a warm and friendly tone") - 10 languages — English, Chinese, Japanese, Korean, German, French, Russian, Spanish, Italian, Portuguese - Streaming support — real-time PCM streaming - Multiple output formats — WAV, MP3, FLAC, PCM Built on the same 1.7B parameter architecture as Qwen3-TTS, using discrete multi-codebook language modeling and a custom 12Hz acoustic tokenizer for high-quality end-to-end speech synthesis.
Try the model with a sample request using the same API shape shown in the reference page.
Natural language description of the desired voice (e.g. "A young cheerful female with a warm tone")
Text to convert to speech
Select the desired language for the speech output. Use Auto for auto-detection.
Select the desired format for the speech output. Supported formats include mp3, opus, flac, wav, and pcm.
The service tier used for processing the request. When set to 'priority', the request will be processed with higher priority (only applies to models that support it).
Tweak the overall style and tone of the conversation by giving some 'master' instructions. (Default: Be a helpful assistant)
Sample from the set of tokens with highest probability such that sum of probabilies is higher than p. Lower values focus on the most probable tokens.Higher values sample more low-probability tokens (Default: 0.9, 0 < top_p ≤ 1)
repetition penalty. Value of 1 means no penalty, values greater than 1 discourage repetition, smaller than 1 encourage repetition. (Default: 1, 0.01 ≤ repetition_penalty ≤ 5)
Sample from the best k (number of) tokens. 0 means off (Default: 0, 0 ≤ top_k < 1000)
maximum length of the newly generated generated text.If explicitly set to None it will be the model's max context length minus input length or 65536, whichever is smaller (Default: empty, 1 ≤ max_new_tokens ≤ 1000000)
A unique identifier representing your end-user, which can help monitor and detect abuse. Avoid sending us any identifying information. We recommend hashing user identifiers.. (Default: empty)
Float that represents the minimum probability for a token to be considered, relative to the probability of the most likely token. Must be in [0, 1]. Set to 0 to disable this. (Default: 0, 0 ≤ min_p ≤ 1)
Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. (Default: 0, -2 ≤ presence_penalty ≤ 2)
Positive values penalize new tokens based on how many times they appear in the text so far, increasing the model's likelihood to talk about new topics. (Default: 0, -2 ≤ frequency_penalty ≤ 2)
How to format the response
temperature to use for sampling. 0 means the output is deterministic. Values greater than 1 encourage more diversity (Default: 0.7, 0 ≤ temperature ≤ 1)
You can add more items with the button
Seed for random number generator. If not provided, a random seed is used. Determinism is not guaranteed. (Default: empty, -9223372036854776000 ≤ seed < 18446744073709552000)
Adjust settings and run the demo to see the model output generated here in real-time.
