MiniMax Speech 2.8 HD is a high-definition text-to-speech model with natural and expressive voice synthesis for premium audio quality. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Ocioso
$0.1por execução·~10 / $1
MiniMax Speech 2.8 HD is a premium text-to-speech model delivering studio-quality audio with enhanced clarity and naturalness. With support for multiple voice presets, emotional tones, and fine-grained audio controls, it produces broadcast-ready speech synthesis for professional applications.
For a faster, more cost-effective option, try MiniMax Speech 2.8 Turbo.
Studio-grade audio quality HD processing delivers richer, cleaner audio with improved naturalness compared to the Turbo version.
Rich voice library Choose from 17+ preset voices spanning different genders, ages, and speaking styles — or use your own custom-trained voice.
Expressive interjections Add natural human sounds like (laughs), (sighs), (coughs), (gasps), and more directly in your text for lifelike delivery.
Emotion control Set the emotional tone of the speech — happy, calm, or other moods — to match your content.
Pronunciation customization Define custom pronunciations for brand names, acronyms, or specialized terms using the pronunciation dictionary.
Full audio control Fine-tune speed, volume, pitch, sample rate, bitrate, channel, and output format for production-ready results.
| Parameter | Required | Description |
|---|---|---|
| text | Yes | The text to convert to speech. Supports interjections like (laughs), (sighs), (coughs) |
| voice_id | Yes | Voice preset or custom voice ID (see Available Voices below) |
| speed | No | Speech speed multiplier (default: 1) |
| volume | No | Volume level (default: 1) |
| pitch | No | Pitch adjustment (default: 0) |
| emotion | No | Emotional tone: happy, calm, etc. |
| pronunciation_dict | No | Custom pronunciation mappings (e.g., Omg/Oh my god) |
| english_normalization | No | Improves number-reading performance in English text |
| sample_rate | No | Audio sample rate |
| bitrate | No | Audio bitrate |
| channel | No | Audio channel (mono/stereo) |
| format | No | Output format |
| language_boost | No | Boost specific language recognition |
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
You can also use a custom voice ID trained via MiniMax Voice Clone.
(laughs), (chuckle), (coughs), (clear-throat), (groans), (breath), (pant), (inhale), (exhale), (gasps), (sniffs), (sighs), (snorts), (burps), (lip-smacking), (humming), (hissing), (emm), (whistles), (sneezes), (crying), (applause)
| Metric | Cost |
|---|---|
| Per 1,000 characters | $0.10 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/minimax/speech-2.8-hd with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Speech 2.8 Hd below.
set -euo pipefail
: "${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-2.8-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/minimax/speech-2.8-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));
}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-2.8-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 2.8 Hd is a MiniMax model for speech synthesis, exposed as a REST API on WaveSpeedAI. MiniMax Speech 2.8 HD is a high-definition text-to-speech model with natural and expressive voice synthesis for premium audio quality. 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 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-2.8-hd.
Speech 2.8 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.
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-2.8-hd.
Reported generation time on WaveSpeedAI is around 5 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.
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.