Minimax Voice Clone creates high-quality voice clones from short reference clips, closely matching tone, accent, and speaking style. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.5per run·~20 / $10
MiniMax Voice Clone is a state-of-the-art voice synthesis and cloning pipeline from MiniMax. It turns a short reference clip into a reusable voice ID, then uses MiniMax Speech models to generate speech that closely matches the speaker’s timbre, accent, and style. The system is built on the MiniMax Speech-02 and Speech-2.6 families, which deliver high-fidelity, multilingual, low-latency TTS for production use.
Now we also supports MiniMax’s latest generation models: Speech 2.6 HD and Speech 2.6 Turbo.
High-Fidelity Voice Cloning Generates speech that is perceptually very close to the reference speaker, with natural prosody, clear pronunciation, and stable timbre across long passages.
Few-Second Voice Adaptation Uses a learnable speaker encoder to extract timbre from just a few seconds of audio, enabling fast, zero-/one-shot voice cloning without transcription.
Emotion and Style Control Exposes parameters for speaking rate, pitch, loudness, and emotion, making it suitable for storytelling, dialogue, gaming characters, and branded voices.
Multilingual & Cross-Lingual Output Supports dozens of languages (30+ in Speech-02 and 40+ in Speech-2.6 on WaveSpeedAI), with robust accent control and smooth code-switching between languages.
Low-Latency Inference Speech-02-Turbo and Speech-2.6-Turbo are optimized for real-time scenarios, with end-to-end latency in the sub-second range and < 250 ms reported for 2.6 in typical interactive settings.
MiniMax Voice Clone is built around a neural TTS pipeline with:
This design combines the clarity of studio-grade TTS with flexible voice cloning, making it suitable for both offline content production and real-time agents.
Upload or paste your reference audio
In the audio field, upload a short, clean voice clip (or paste a direct URL). Around 5–20 seconds of speech without background music works best.
Set custom_voice_id
Choose a new, descriptive ID (for example: Alice-001).
This ID must be unique across your account.
If you reuse an existing ID when creating a new clone, the request will fail with a “voice clone voice id duplicate” error.
Select the speech model: Such as speech-02-hd.
Enter the output text
In the text field, type what you want the cloned voice to say.
Example: “Hello! Welcome to WaveSpeedAI. This is a preview of your cloned voice.”
Turn on need_noise_reduction if your reference audio has background noise.
Turn on need_volume_normalization to even out volume differences.
Adjust the accuracy slider if available: higher values make cloning closer to the reference, lower values make it more forgiving to noisy audio.
The custom_voice_id you used is now available for reuse in the supported MiniMax speech models.
Your cloned voice IDs can be used directly with the following MiniMax speech models on WaveSpeedAI:
To keep your cloned voice reusable in the long term:
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/voice-clone with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Voice Clone below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/minimax/voice-clone" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"audio": "https://example.com/your-audio.mp3",
"model": "speech-02-hd",
"need_noise_reduction": false,
"need_volume_normalization": false,
"accuracy": 0.7,
"text": "Hello! Welcome to Wavespeed! This is a preview of your cloned voice. I hope you enjoy it!",
"language_boost": "Chinese"
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("minimax/voice-clone", {
"audio": "https://example.com/your-audio.mp3",
"model": "speech-02-hd",
"need_noise_reduction": false,
"need_volume_normalization": false,
"accuracy": 0.7,
"text": "Hello! Welcome to Wavespeed! This is a preview of your cloned voice. I hope you enjoy it!",
"language_boost": "Chinese"
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"minimax/voice-clone",
{
"audio": "https://example.com/your-audio.mp3",
"model": "speech-02-hd",
"need_noise_reduction": false,
"need_volume_normalization": false,
"accuracy": 0.7,
"text": "Hello! Welcome to Wavespeed! This is a preview of your cloned voice. I hope you enjoy it!",
"language_boost": "Chinese"
}
)
print(output["outputs"][0]) # → URL of the generated outputVoice Clone is a MiniMax model for AI inference, exposed as a REST API on WaveSpeedAI. Minimax Voice Clone creates high-quality voice clones from short reference clips, closely matching tone, accent, and speaking style. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/minimax/minimax-voice-clone.
Voice Clone starts at $0.50 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `audio`, `accuracy`, `custom_voice_id`, `language_boost`, `model`, `need_noise_reduction`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/minimax/minimax-voice-clone.
Average end-to-end generation time on WaveSpeedAI is around 14 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (MiniMax). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.