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Compare text-to-speech APIs live, side by side

Generate the same speech with multiple providers and hear the difference for yourself. Compare voices, pronunciation, pacing, prosody, expressiveness, and latency using the APIs and models you actually want to evaluate.

Who supports what feature

Feature support for the models Soniox Compare runs, as declared by the provider integrations in the app. See which models and voices support the languages, streaming, voice controls, and other capabilities you need.

FeatureSoniox
tts-rt-v2
OpenAI
gpt-4o-mini-tts
ElevenLabs
eleven_v3
Fish Audio
s2.1-pro
Inworld
inworld-tts-2
xAI
tts-v1
Google
gemini-3.8-flash-tts
Cartesia
sonic-3.6
Azure
dragon-hd-omni
Smallest AI Pro
lightning_v3.1_pro
Languages60+5770+8394209244?31
Streaming audio output
Streaming text input
Multilingual voice
Voice cloning
Timestamps
Pronunciation control
Expressive control
SupportedPartialNot supported

Who supports what language

The 130 languages spoken by more than a million people, and which providers can speak them. Pin the ones your product needs.

LanguageSoniox
tts-rt-v2
OpenAI
gpt-4o-mini-tts
ElevenLabs
eleven_v3
Fish Audio
s2.1-pro
Inworld
inworld-tts-2
xAI
tts-v1
Google
gemini-3.8-flash-tts
Cartesia
sonic-3.6
Azure
dragon-hd-omni
Smallest AI Pro
lightning_v3.1_pro
en
zh
hi
es
ar
fr
bn
pt
id
ur
ru
de
SupportedNot supported

Compare is open source

The complete source code is on GitHub under the MIT License.

Run the same comparison yourself

Inspect every provider integration, see exactly which models, voices, and settings are used, and check how audio is generated and handled.

Clone the repository, add your own API keys, and run it locally. Every provider receives the same input through its official API. A missing key only disables that provider.

Clone the repo on GitHub
git clone https://github.com/soniox/soniox-compare
cd soniox-compare
for app in stt tts translate; do
  cp "$app/.env.example" "$app/.env"
done
./dev.sh

Contribute

Add a provider, add a model or voice, improve an integration, or help make TTS comparisons more useful for real applications.

Start contributing
The soniox-compare repository on GitHub

Why benchmarks mislead

TTS benchmarks make controlled comparisons possible, but they can only evaluate the voices, prompts, and conditions they choose. The output can be very different when you use your own voice, content, and requirements.

The same model can sound very different

Voice selection is a major part of TTS quality. A benchmark result can depend on which voice was used, whether voices were standardized, and whether the evaluation measures the model independently of the voice itself.

Your application may need a specific voice, style, language, accent, or personality. A model’s overall benchmark score doesn’t tell you how that particular combination will sound.

The details matter

A TTS system can sound natural overall and still get the things that matter to your product wrong.

Pronunciation, names, numbers, dates, abbreviations, technical terms, emphasis, pauses, pacing, and prosody can all change the quality of the output. Some applications need natural conversation. Others need precise pronunciation, consistent delivery, or a particular style.

A benchmark score compresses these different qualities into a result. Listening to the actual output shows you the differences.

I hear theirthere new offer is on hold, for now.?

A leaderboard can’t test your requirements

Benchmarks use fixed prompts and controlled evaluation conditions so providers can be compared fairly. That makes the results reproducible, but it also means the test is necessarily limited.

Your product has its own voices, content, languages, latency requirements, and edge cases.

The only way to know how a provider performs for those requirements is to test them.

Hear what you’re actually going to ship

Give every provider the same input and listen to the generated audio side by side.

Compare the things a number can’t tell you: how the voice sounds, how it handles your content, where it pauses, what it emphasizes, how it pronounces difficult words, and how quickly the audio starts.

English isn’t enough

Supporting a language doesn’t mean the output sounds equally natural in that language. Pronunciation, names, numbers, accents, and language-specific prosody can expose weaknesses that an English-focused benchmark never shows.

A benchmark can support many languages and still tell you very little about how the voice will sound when your product actually speaks them.

World map with countries where English is an official language highlighted
Countries where English is an official language
World map with countries where English is not an official language highlighted
Countries where it is not

Methodology

Same input. Every provider. Their real API.

Same text, every provider

Your browser sends the same text to the Compare backend. The backend opens one session per selected provider, using that provider’s official TTS API and the model and voice listed in the feature table.

Same settings wherever supported

Every provider receives the same input and the same requested settings wherever supported. Provider-specific options are used according to each integration, and unsupported options are dropped for that provider only.

Audio returned as generated

Audio is returned as generated by each provider. Compare does not rewrite, normalize, enhance, or otherwise alter the generated speech before you hear it.

No hidden dataset

There is no hidden benchmark dataset and no aggregate quality score. You provide the input, so you can test the speech your application actually needs to generate.

Heard as it is generated

Audio is shown as it is generated, so you can compare both the resulting speech and the experience of receiving it.

No universal winner

Compare does not claim that one TTS provider is universally better. It lets you evaluate the voices and models against the requirements of your own product.

Frequently asked questions

Which text-to-speech API sounds best?
It depends on the voice, the content, and the language. A provider that sounds best for one voice and script can sound worse on the next, and names, numbers, and pacing can change the result. That is why this tool sends your text to every provider at once, so you listen side by side on the content you will actually use.
Why don’t you publish a quality leaderboard?
A leaderboard compresses voices, prompts, and conditions into one score. Your product has its own voices, content, languages, and requirements, and a score cannot tell you how that combination will sound. Listening to the generated audio side by side shows you the differences instead.
Is the comparison fair to every provider?
Every provider receives the same text through its official API, using the model and voice listed in the feature table. Each provider only gets the options it supports, and audio is played as returned. The code is open, so you can check every integration and run it yourself.
Can I add my own provider, model, or voice?
Yes. Each provider is a single Python module with a generate function, and its model and voice are set in that module. Write the module, register it in the provider map, and add its API key to the environment file. The frontend picks it up from the backend without any change.
Which languages are supported?
Language support is per provider. The tool only offers a language for a provider that supports it, and the language row in the feature table shows each provider’s documented total.
How is latency measured?
It is not scored. Every playback makes a live API request, so you experience how quickly each provider’s audio starts. Network distance, provider regions, and load all affect what you hear, so the tool does not publish latency numbers.