How to Use the Eleven Turbo v2.5 API: text to speech integration guide (2026)
Learn how to call the Eleven Turbo v2.5 API on NamiFusion: parameters, pricing (from ≈$0.010) and runnable copy-paste code — try it in the playground first.
Eleven Turbo v2.5 is a text to speech model by ElevenLabs: Our high quality, low latency model in 32 languages. Best for developer use cases where speed matters and you need non-English languages. On NamiFusion you can try it in the playground (exact quote shown before you submit), then call it through one unified REST API — a typical run costs about $0.010.
TL;DR
· Task type: text to speech, provided by ElevenLabs
· Pricing: about $0.010 per typical run ($1 = 100 credits), pay-as-you-go
· Getting started: playground (exact quote before submit) → create an API key → one POST request
· Tunable parameters: 4 (see the table below)
· No platform watermark; commercial use allowed (per the Terms of Service)
What can you build with Eleven Turbo v2.5?
Voiceovers and narration: generate multi-language voices for short videos, courses and ads.
Audio content production: turn articles, news and fiction into publishable audio at scale.
Product voice interfaces: consistent branded voices for apps and devices.
How do you call this API?
1. Sign up on NamiFusion and create a key on the API Keys page (free credits on signup).
2. Submit a task with the cURL example below, passing your key as a Bearer token.
3. Poll the task status with the returned task_uuid and read the output URLs when completed.
# 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"What parameters does it take?
voice_id (声音id): required
language_code (ISO 639-1语言code): optional
similarity_boost (Similarity Boost): optional, default 0.75
stability (Stability): optional, default 0.5
How much does it cost?
Pay-per-use in credits. A typical run costs about $0.010 ($1 = 100 credits); the exact price varies with parameters like resolution or duration, and the playground shows the exact quote before you submit.
Eleven 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_idoptions, making it easy to match different brands, characters, or content styles. - Fine-grained voice control: Tune
similarityandstabilityto balance speaker likeness, clarity, and consistency. - Improved English normalization:
use_speaker_boosthelps 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
| Item | Details |
|---|---|
| Model architecture | Text-to-speech（TTS） |
| Model name | Turbo V2.5 |
| Input format | Text（string） |
| Output format | Audio |
| Maximum input length | 10,000 characters |
| Tokenization rule | Each character counts as 1 token |
| Voice selection | Set via voice_id such as Alice, Callum, Gigi, and others |
| Similarity control | similarity: 0.0–1.0; higher values increase target voice likeness but may introduce artifacts |
| Stability control | stability: 0.0–1.0; higher values generally improve delivery consistency |
| English enhancement | use_speaker_boost: improves normalization and reading of English numbers and units |
| Pause control | Insert <#x#> between words to control pauses from 0.01 to 99.99 seconds |
| Latency | Fast inference suitable for production workflows |
| Cold start | None |
| Language support | Multilingual 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.
Welcome to our advanced text-to-speech system! Experience high-quality voice synthesis with natural pronunciation and clear articulation.Today we shipped 12,450 units in Q3, with delivery scheduled at 8:30 AM on October 15th.Please wait <#1.2#> your verification code is 4829 <#0.8#> and will expire in five minutes.
💰 Pricing
| Item | Price |
|---|---|
| Text-to-speech | $0.05 per 1,000 characters |
FAQ
Can I try it for free first?+
Signup gives you free credits, but they currently apply only to selected in-app face-swap features — this model is pay-as-you-go. The playground still lets you try it without code, with the exact quote shown before you submit.
Can I use the output commercially? Is there a watermark?+
Yes, outputs are yours to use commercially, and NamiFusion adds no platform watermark — subject to the Terms of Service and applicable law.
What is the content policy?+
NamiFusion is an unfiltered engine: no arbitrary restrictions and NSFW-friendly, but illegal content and non-consensual use of real people are prohibited — see the Terms of Service.
How long does a Eleven Turbo v2.5 task take?+
It depends on parameters — images usually take seconds, videos tens of seconds to minutes. The API returns a task_uuid for polling.
What are the resolution and duration limits?+
See the parameter table above — each model lists its available resolution and duration options there and in the playground.