Simba 3.2 is #1 on Artificial Analysis, at the lowest price and sub-100ms latency. Don't take our word for it — hear it against a competing flagship and pick the winner.
Two voices read it. You pick the winner.
Our flagship streaming-native English model, with the lowest time to first byte in the Simba family, finer-grained emotional control, SSML prosody, and a curated voice set.
simba-3.2English today24 kHzDelivery preview
Five expressions. One line.
“Every moment of light and dark is a miracle.”
Speech is more than clean audio. Simba models identity, expression, and language as one continuous signal, then serves it fast enough for real conversation.
Create a reusable voice from a short, consented reference clip. Self-serve cloning on Simba 3.0 preserves the speaker's identity across new scripts.
simba-3.02 playable samplessimba-3.0Voice identity
Reference in. Same speaker out.
Reference
Original speaker
Clone
Simba 3.0 output
Consent-first cloning with a reusable voice ID
Direct the same line toward neutral, calm, cheerful, energetic, or sad delivery. Simba 3.2 shapes rhythm and tone with SSML emotion control.
simba-3.25 playable samplessimba-3.2Expression
Same words. Different feeling.
Use Simba 3.0 for English, German, Mexican Spanish, French, Italian, and Brazilian Portuguese. Each sample uses a voice cataloged for that locale.
simba-3.06 playable samplessimba-3.0Six validated locales
Streaming speech beyond English.
A single API to access all SpeechifyAI models. Streaming, voice cloning, emotion control — everything in a few lines of code.
curl -X POST https://api.speechify.ai/v1/audio/speech \
-H "Authorization: Bearer $SPEECHIFY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Hello, world.",
"voice_id": "george",
"audio_format": "mp3"
}'We're a research lab focused on speech synthesis, voice understanding, and audio intelligence. Our work spans fundamental research in neural speech generation, zero-shot voice cloning, and emotional expression modeling — turning the nuances of human speech into something machines can learn and reproduce.