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minimax/speech-2.6-hd

Minimax Speech 2.6 HD: Ultra-human, low-latency (< 250ms) TTS with voice cloning, text normalization and support for 40+ languages. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Text to Speech
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$0.1per run·~10 / $1

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README

MiniMax Speech 2.6 HD

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

Features

  • Multilingual upgrade: Stronger 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: Control across language, accent, style, and emotion—preserves cross-language and regional accents and “age” timbre with high fidelity.
  • Global language set (40+): Expanded catalog including Bulgarian, Danish, Hebrew, Malay, Persian, Slovak, Swedish, Croatian, Filipino, Hungarian, Norwegian, Slovenian, Catalan, Nynorsk, Tamil, Afrikaans, and more—ideal 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 numbers/units (e.g., “$1,299” → “one thousand two hundred ninety-nine dollars”).
  • sample_rate (Hz) 22050 / 24000 / 44100 / 48000. Tip: 44.1 kHz for music/podcasts; 48 kHz for video.
  • bitrate (bps for MP3/OGG) 64k / 96k / 128k / 192k / 256k / 320k. Tip: ≥192k for distribution; 96–128k for previews.
  • channel: mono or stereo Mono is smaller/clearer for speech; stereo for spatial mixes.
  • format: mp3, wav, ogg, flac, wav is lossless (larger); mp3 is compact and web-friendly. Also supports streaming PCM output for real-time playback.
  • language_boost (IETF code: en, zh, ja, …) Prioritizes a primary language in mixed-language inputs.

Prosody controls

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

Pricing

  • Price: $0.10 / 1,000 characters

Quick examples

  • 1,000 chars → $0.10
  • 2,500 chars → $0.10 × 2.5 = $0.25
  • 10,000 chars → $1.00

Typical Use Cases

Short-video and ad voiceovers, e-learning/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
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Speech 2.6 Hd API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/speech-2.6-hd 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 Hd below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "text": "A clear example input",
    "voice_id": "example",
    "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-hd" \
  -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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 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' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/minimax/speech-2.6-hd";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "text": "A clear example input",
        "voice_id": "example",
        "speed": 1,
        "volume": 1,
        "pitch": 0,
        "emotion": "happy",
        "english_normalization": false,
        "sample_rate": 8000,
        "bitrate": 32000,
        "channel": "1",
        "format": "mp3",
        "language_boost": "Chinese"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  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": "example",
    "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-hd", 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 = 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", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Speech 2.6 Hd API — Frequently asked questions

What is the Speech 2.6 Hd API?

Speech 2.6 Hd is a MiniMax model for speech synthesis, exposed as a REST API on WaveSpeedAI. Minimax Speech 2.6 HD: Ultra-human, low-latency (< 250ms) TTS with voice cloning, text normalization and support for 40+ languages. 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 Hd 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 Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/minimax/minimax-speech-2.6-hd.

How much does Speech 2.6 Hd cost per run?

Speech 2.6 Hd starts at $0.1 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 Hd 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-hd.

How long does Speech 2.6 Hd take to generate?

Reported generation time on WaveSpeedAI is around 4 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.

Can I use Speech 2.6 Hd outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (MiniMax). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — minimax/speech-2.6-hd for AI agents and LLMs