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KittenTTS

OSS

The lightweight/edge option: ONNX inference, sub-100 MB downloads, 8 built-in voices - trades voice cloning and multilinguality for footprint.

Among the 46 text-to-speech tools we track, KittenTTS has the 43rd-widest language coverage.

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Facts verified Jul 20, 2026Website →

What we know about KittenTTS

KittenTTS is a text-to-speech apis platform: the lightweight/edge option: ONNX inference, sub-100 MB downloads, 8 built-in voices - trades voice cloning and multilinguality for footprint. This profile tracks what we have verified about KittenTTS, each fact linked to a primary source and dated.

KittenTTS does not publish a public per-minute rate we have been able to verify, so the price figure here stays blank until we can confirm one. We would rather show nothing than a guessed number; if you have a current KittenTTS quote, it is the fastest way for us to close that gap.

On capabilities, KittenTTS covers self-host / on-prem option, and does not offer instant voice cloning. Each of those is verified against KittenTTS's own docs or dashboard, not marketing copy.

In total we track 9 verified facts for KittenTTS today, and add coverage as the ingestion pass revisits it. Where a number is a vendor claim rather than our own measurement, it is labeled as such on the KittenTTS fact sheet below, and each row links the primary source it came from so you can check our work.

Whether KittenTTS is the right call depends on your use case more than any single spec, which is why the head-to-head verdicts below score it per scenario rather than crowning one overall winner. Use the fact sheet for the raw numbers, and the matchups for how KittenTTS actually fares against the platforms buyers most often weigh it against.

Fact sheet

Capabilities
Capabilities facts
Instant voice cloning✗ NoJul 20
Languages supported1 languagesJul 20
Compliance & trust
Compliance & trust facts
Self-host / on-prem option✓ YesJul 20
Model weights licenseApache-2.0Jul 20
Build experience
Build experience facts
Official SDKsPython (pip wheel, ONNX)Jul 20
Commercial
Commercial facts
Model size (parameters)15M (nano), 40M (micro), 80M (mini)Jul 20
Hardware to self-hostCPU only, no GPU requiredJul 20
Project maintenance statusactiveJul 20
GitHub stars15,187 starsJul 20

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