Google Gemini 2.5 Flash Text-to-Speech delivers fast, natural multi-speaker voice synthesis with 30+ voices across 24 languages at lower cost. Perfect for dialogues, conversations, and multilingual content. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.04per run·~25 / $1
Gemini 2.5 Flash Text-to-Speech is Google's fast, cost-efficient multi-speaker speech synthesis model. It turns written dialogue into natural, expressive audio with support for multiple speakers and distinct voices in a single generation — at half the cost of the Pro version. Ideal for high-volume TTS workflows like podcasts, conversations, audiobooks, and voiceover production.
Fast and affordable Optimized for speed and cost-efficiency, delivering natural speech at half the price of Gemini 2.5 Pro TTS.
Multi-speaker dialogue Assign different voices to different speakers and generate a natural-sounding conversation in one pass — no need to stitch separate audio clips together.
Expressive, natural voices The voices carry natural intonation, pacing, and emotional range for lifelike results.
Multi-language support Supports a wide range of languages including Arabic (Egypt), Bangla (Bangladesh), Dutch (Netherlands), English (India), English (United States), French (France), German (Germany), Hindi (India), Indonesian (Indonesia), and more.
Flexible speaker setup Add as many speakers as your script needs, each with their own named voice. Simply write dialogue with speaker labels and the model handles the rest.
| Parameter | Required | Description |
|---|---|---|
| text | Yes | The script or dialogue text. Use "Speaker: line" format for multi-speaker content. |
| language | Yes | Language and locale for synthesis (e.g., English (United States), French (France)). |
| speakers | Yes | A list of speaker entries, each with a speaker name and a voice selection. |
$0.04 per 1,000 characters of input text.
| Text Length | Cost |
|---|---|
| 500 characters | $0.04 |
| 1,000 characters | $0.04 |
| 2,500 characters | $0.12 |
| 5,000 characters | $0.20 |
| 10,000 characters | $0.40 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/gemini-2.5-flash/text-to-speech with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Gemini 2.5 Flash Text To Speech below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"text": "A clear example input",
"language": "English (United States)"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/google/gemini-2.5-flash/text-to-speech" \
-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/google/gemini-2.5-flash/text-to-speech";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"text": "A clear example input",
"language": "English (United States)"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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",
"language": "English (United States)",
"speakers": []
}
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/google/gemini-2.5-flash/text-to-speech", 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)Gemini 2.5 Flash Text To Speech is a Google model for audio generation, exposed as a REST API on WaveSpeedAI. Google Gemini 2.5 Flash Text-to-Speech delivers fast, natural multi-speaker voice synthesis with 30+ voices across 24 languages at lower cost. Perfect for dialogues, conversations, and multilingual content. 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 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/google/google-gemini-2.5-flash-text-to-speech.
Gemini 2.5 Flash Text To Speech starts at $0.040 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: `language`, `speakers`, `text`. 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/google/google-gemini-2.5-flash-text-to-speech.
Median end-to-end generation time on WaveSpeedAI is around 24 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Google). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.