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Speech 2.6 Turbo

minimax /

Minimax Speech 2.6 Turbo is a Text-to-Speech model offering ultra-human voice cloning, industry-leading text normalization, sub-250ms latency and 40+ language support. Pricing: $0.06 per 1000 characters. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-audio
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$0.06每次運行·~16 / $1

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README

MiniMax Speech 2.6 Turbo

High-definition Text-to-Speech (TTS) with natural pronunciation and crisp articulation. Supports multiple built-in voices and custom cloned voices, adjustable speed, volume, and pitch, and coverage of 40+ languages for professional audio creation.

Features

  • Multilingual leap: Substantially improved English and overall multilingual similarity, accuracy, and rhythm vs. Speech 02; seamless switching across 40 languages for meetings, podcasts, and daily dialog.
  • Lifelike tone replication: Cross-language, accent, style, and emotion control with industry-leading nuance—including cross-language accent retention, regional accent preservation, and special age voice replication.
  • Global language set (40+): Expanded library including (new adds) Bulgarian, Danish, Hebrew, Malay, Persian, Slovak, Swedish, Croatian, Filipino, Hungarian, Norwegian, Slovenian, Catalan, Nynorsk, Tamil, Afrikaans, and more—great for cross-border commerce, customer support, and localized marketing.
  • Real-time streaming capabilities: generate and play audio as it’s being synthesized, enabling low-latency experiences for live or interactive applications.

How to Use

1) Choose a Voice (voice_id)

Use either a custom voice you trained (voice cloning) or a built-in system voice (case-sensitive):

Wise_Woman, Friendly_Person, Inspirational_girl, Deep_Voice_Man, Calm_Woman,
Casual_Guy, Lively_Girl, Patient_Man, Young_Knight, Determined_Man, Lovely_Girl,
Decent_Boy, Imposing_Manner, Elegant_Man, Abbess, Sweet_Girl_2, Exuberant_Girl

2) Set Audio Parameters (mapped to the UI dropdowns)

  • english_normalization (boolean) Improves English text normalization, especially for number reading (e.g., “$1,299” → “one thousand two hundred ninety-nine dollars”).
  • sample_rate (Hz) Common: 22050, 24000, 44100, 48000. Tips: 44.1 kHz for music/podcasts; 48 kHz for video post-production.
  • bitrate (bps for MP3/OGG) 64k / 96k / 128k / 192k / 256k / 320k. Tips: ≥192k for distribution; 96–128k for previews.
  • channel: mono or stereo Mono is smaller/clearer for speech; stereo when spatialization is desired.
  • format: mp3, wav, ogg, flac, wav is lossless (bigger files); mp3 is compact and web-friendly. Also supports streaming PCM output for real-time playback.
  • language_boost (IETF code like en, zh, ja …) Prioritize the main language in mixed-language inputs.

Prosody controls

  • speed: speaking rate (e.g., 0.8–1.2).
  • volume: gain (unit depends on API; typically linear or dB).
  • pitch: pitch shift (semitones/cents or normalized value).

Price

Price: $0.06 / 1,000 characters

Typical Use Cases

  • Short-video and ad voiceovers, e-learning and courseware, AI assistants and IVR, podcasts/audiobooks, cross-border e-commerce localization.

Best-Practice Presets (optional)

  • Video voiceover: format=wav, sample_rate=48000, channel=mono, english_normalization=true.
  • Web preview: format=mp3, sample_rate=44100, bitrate=128000, channel=mono.
  • Podcast: format=mp3, sample_rate=44100, bitrate=192000–320000, channel=stereo if mixing music.
提示:本網站部分功能由第三方 AI 模型提供支援。

Speech 2.6 Turbo API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/speech-2.6-turbo with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Speech 2.6 Turbo below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "text": "A clear example input",
    "voice_id": "Wise_Woman",
    "speed": 1,
    "volume": 1,
    "pitch": 0,
    "emotion": "happy",
    "english_normalization": false,
    "sample_rate": 8000,
    "bitrate": 32000,
    "channel": "1",
    "format": "mp3",
    "language_boost": "Chinese"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/minimax/speech-2.6-turbo" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/minimax/speech-2.6-turbo";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "text": "A clear example input",
        "voice_id": "Wise_Woman",
        "speed": 1,
        "volume": 1,
        "pitch": 0,
        "emotion": "happy",
        "english_normalization": false,
        "sample_rate": 8000,
        "bitrate": 32000,
        "channel": "1",
        "format": "mp3",
        "language_boost": "Chinese"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "text": "A clear example input",
    "voice_id": "Wise_Woman",
    "speed": 1,
    "volume": 1,
    "pitch": 0,
    "emotion": "happy",
    "english_normalization": False,
    "sample_rate": 8000,
    "bitrate": 32000,
    "channel": "1",
    "format": "mp3",
    "language_boost": "Chinese"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/minimax/speech-2.6-turbo", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Speech 2.6 Turbo API — Frequently asked questions

What is the Speech 2.6 Turbo API?

Speech 2.6 Turbo is a MiniMax model for audio generation, exposed as a REST API on WaveSpeedAI. Minimax Speech 2.6 Turbo is a Text-to-Speech model offering ultra-human voice cloning, industry-leading text normalization, sub-250ms latency and 40+ language support. Pricing: $0.06 per 1000 characters. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Speech 2.6 Turbo API?

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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/minimax/minimax-speech-2.6-turbo.

How much does Speech 2.6 Turbo cost per run?

Speech 2.6 Turbo starts at $0.060 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.

What inputs does Speech 2.6 Turbo accept?

Key inputs: `bitrate`, `channel`, `emotion`, `enable_base64_output`, `enable_sync_mode`, `english_normalization`. 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-speech-2.6-turbo.

How long does Speech 2.6 Turbo take to generate?

Median end-to-end generation time on WaveSpeedAI is around 5 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Speech 2.6 Turbo outputs commercially?

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.

Speech 2.6 Turbo | Realistic Voice & TTS API | WaveSpeedAI