Speech synthesis models
Our models are built for different use cases — from expressive English narration to native-quality multilingual synthesis.
Simba 3.2
model="simba-3.2"Streaming-native speech with <100ms first byte and rich expressivity
Our flagship streaming-native English model. First byte in <100ms, finer-grained emotional control, SSML prosody, and every English voice in the catalog, your cloned voices included.
- Streaming-native architecture
- Emotional expression
- Every English voice in the catalog
- Self-serve voice cloning
- SSML prosody control
Emotion Control
Direct the same line toward neutral, calm, cheerful, energetic, or sad delivery. Simba 3.2 shapes rhythm and tone with SSML emotion control.
“The quick brown fox jumped over the lazy dog.”
Simba 3.0
model="simba-3.0"Streaming-native synthesis beyond English
Streaming-native synthesis in English, German, Spanish, French, Italian, and Brazilian Portuguese. Routing happens automatically by language, and zero-shot voice cloning works self-serve.
- Streaming-native architecture
- 7 supported locales
- Zero-shot voice cloning
- Emotional expression
- SSML prosody control
- en-USEnglish
- de-DEGerman
- es-MXSpanish (Mexico)
- es-ESSpanish (Spain)Cloned voice required
- fr-FRFrench
- it-ITItalian
- pt-BRPortuguese (BR)
Stock voices are available for six locales. Check GET /v1/voices before building a language menu. Need a language outside this set? We cover 30+ languages in total - talk to us about reaching them.
Multilingual Synthesis
Use Simba 3.0 for English, German, Mexican Spanish, French, Italian, and Brazilian Portuguese. Each sample uses a voice cataloged for that locale.
English
en-US
German
de-DE
Spanish
es-MX
French
fr-FR
Italian
it-IT
Portuguese
pt-BR
Zero-Shot Voice Cloning
Create a reusable voice from a short, consented reference clip. Self-serve cloning on Simba 3.2 and Simba 3.0 preserves the speaker's identity across new scripts.
All models, one API
Access every model through the same endpoint. Switch between models with a single parameter change.
from speechify import Speechify
client = Speechify() # uses SPEECHIFY_API_KEY env var
response = client.tts.audio.speech(
input='<speak><speechify:style emotion="cheerful">Every moment of light and dark is a miracle.</speechify:style></speak>',
voice_id="geffen_32",
model="simba-3.2",
audio_format="mp3",
)
with open("output.mp3", "wb") as f:
f.write(response.audio_data)