Eleven Turbo v2.5

eleven_turbo_v2_5

Our high quality, low latency model in 32 languages. Best for developer use cases where speed matters and you need non-English languages.

Examples

Eleven Turbo v2.5 example 1

Parameters

NameTypeDefaultConstraintsDescription
voice_id *声音idtext
language_codeISO 639-1语言codetext
similarity_boostSimilarity Boostslider0.750 ~ 1 · step 0.05
stabilityStabilityslider0.50 ~ 1 · step 0.05

Output fields

FieldTypeDescription
audio_urlstring

API

Call this model through one unified REST API. Get a key on the API Keys page.

cURL
# 1) Submit — returns { "task_uuid": "..." }
curl -X POST "https://www.namifusion.com/api/v1/marketplace/run/eleven_turbo_v2_5" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input": {
    "voice_id": "JBFqnCBsd6RMkjVDRZzb",
    "language_code": "en",
    "similarity_boost": 0.8,
    "stability": 0.55
  }
}'

# 2) Poll until status is "completed", then read the output URLs
curl "https://www.namifusion.com/api/v1/marketplace/run/tasks/TASK_UUID" \
  -H "Authorization: Bearer YOUR_API_KEY"
Python
import time, requests

API_KEY = "YOUR_API_KEY"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# 1) Submit
resp = requests.post(
    "https://www.namifusion.com/api/v1/marketplace/run/eleven_turbo_v2_5",
    headers=HEADERS,
    json={
        "input": {
            "voice_id": "JBFqnCBsd6RMkjVDRZzb",
            "language_code": "en",
            "similarity_boost": 0.8,
            "stability": 0.55
        }
    },
)
resp.raise_for_status()  # 401/402/429/5xx stop here instead of polling a bad task
task = resp.json()

# 2) Poll until a terminal state (completed / failed / cancelled).
#    This model is allowed up to 300s server-side.
deadline = time.time() + 360
while task.get("status") not in ("completed", "failed", "cancelled"):
    if time.time() > deadline:
        raise TimeoutError(f"still {task.get('status')} — keep the task_uuid and poll later")
    time.sleep(3)
    poll = requests.get(f"https://www.namifusion.com/api/v1/marketplace/run/tasks/{task['task_uuid']}", headers=HEADERS)
    poll.raise_for_status()
    task = poll.json()

print(task["status"], task.get("output"))
JavaScript
const API_KEY = "YOUR_API_KEY";
const HEADERS = { Authorization: `Bearer ${API_KEY}` };

// 1) Submit
const resp = await fetch("https://www.namifusion.com/api/v1/marketplace/run/eleven_turbo_v2_5", {
  method: "POST",
  headers: { ...HEADERS, "Content-Type": "application/json" },
  body: JSON.stringify({
    "input": {
      "voice_id": "JBFqnCBsd6RMkjVDRZzb",
      "language_code": "en",
      "similarity_boost": 0.8,
      "stability": 0.55
    }
  }),
});
if (!resp.ok) throw new Error(`submit failed: ${resp.status} ${await resp.text()}`);
let task = await resp.json();

// 2) Poll until a terminal state (completed / failed / cancelled).
//    This model is allowed up to 300s server-side.
const deadline = Date.now() + 360 * 1000;
while (!["completed", "failed", "cancelled"].includes(task.status)) {
  if (Date.now() > deadline) throw new Error(`still ${task.status} — keep the task_uuid and poll later`);
  await new Promise((r) => setTimeout(r, 3000));
  const poll = await fetch(`https://www.namifusion.com/api/v1/marketplace/run/tasks/${task.task_uuid}`, { headers: HEADERS });
  if (!poll.ok) throw new Error(`poll failed: ${poll.status}`);
  task = await poll.json();
}

console.log(task.status, task.output);

Documentation

Turbo V2.5

A fast, cost-efficient text-to-speech model for natural and expressive voice generation.

Turbo V2.5 is an ElevenLabs text-to-speech model available on WaveSpeed AI. It is designed for teams that need strong voice quality, fast turnaround, and predictable cost, making it well suited for production-grade audio generation. With no cold starts and ready-to-use inference performance, it fits both real-time and batch content workflows.

🚀 Key Features

  • Natural, expressive speech: Produces clear pronunciation, smooth pacing, and humanlike prosody for polished voice output.
  • Fast generation with no cold start: Delivers responsive performance for high-throughput production pipelines.
  • Rich voice selection: Supports a broad set of voice_id options, making it easy to match different brands, characters, or content styles.
  • Fine-grained voice control: Tune similarity and stability to balance speaker likeness, clarity, and consistency.
  • Improved English normalization: use_speaker_boost helps with English numbers, dates, times, and measurement-heavy scripts.
  • Affordable pricing: Low per-character cost makes it practical for both prototyping and scaled deployment.

🛠️ Technical Specifications

ItemDetails
Model architectureText-to-speech(TTS)
Model nameTurbo V2.5
Input formatText(string)
Output formatAudio
Maximum input length10,000 characters
Tokenization ruleEach character counts as 1 token
Voice selectionSet via voice_id such as Alice, Callum, Gigi, and others
Similarity controlsimilarity: 0.0–1.0; higher values increase target voice likeness but may introduce artifacts
Stability controlstability: 0.0–1.0; higher values generally improve delivery consistency
English enhancementuse_speaker_boost: improves normalization and reading of English numbers and units
Pause controlInsert <#x#> between words to control pauses from 0.01 to 99.99 seconds
LatencyFast inference suitable for production workflows
Cold startNone
Language supportMultilingual voice support, with strong English reading performance

Sample prompts

Note: This is a text-to-speech model, so the examples below are sample input scripts.

  1. Welcome to our advanced text-to-speech system! Experience high-quality voice synthesis with natural pronunciation and clear articulation.
  2. Today we shipped 12,450 units in Q3, with delivery scheduled at 8:30 AM on October 15th.
  3. Please wait <#1.2#> your verification code is 4829 <#0.8#> and will expire in five minutes.

💰 Pricing

ItemPrice
Text-to-speech$0.05 per 1,000 characters

💡 Best Use Cases

  • Voiceovers and narration: Ideal for explainer videos, tutorials, podcasts, and branded media.
  • Business audio automation: Useful for alerts, announcements, customer messaging, and information playback.
  • Finance and data-heavy scripts: Especially effective for content with numbers, dates, times, and measurements.
  • Multi-voice digital content: Great for teams producing character-driven or brand-specific audio at scale.

🔗 Related Models

  • Elevenlabs Turbo V2: An earlier Turbo-series option for users comparing speed, quality, and cost.
  • Elevenlabs Voice Changer: A complementary model for voice transformation workflows.