Kokoro vs Chatterbox
Both are alternatives to ElevenLabs. Here's how they stack up — verified facts, no spin.
Also searched as Chatterbox vs Kokoro — same comparison, one verdict.
Kokoro and Chatterbox are closely matched on ownership (94 vs 92) — this one comes down to pricing and to which trade-offs below you can live with.
Kokoro
TOP PICK82M parameters, Apache-2.0, and the top of the TTS leaderboard.
Kokoro is a remarkably small open text-to-speech model — around 82 million parameters and a roughly 300MB footprint — that nonetheless ranks at the top of the TTS Arena leaderboard. It is released under Apache-2.0, so commercial use is free and unencumbered. Because it is small it runs faster than real time on modest hardware, including a cheap rented GPU, which makes it the most practical drop-in replacement for a per-character API for most teams.
Chatterbox
MIT-licensed voice cloning that beat ElevenLabs in a blind test.
Chatterbox is an open text-to-speech model under the MIT licence with zero-shot voice cloning from roughly five seconds of reference audio, emotion/intensity control, and support for around 23 languages. In a published blind listening comparison, participants preferred Chatterbox-Turbo about 65% of the time against ElevenLabs' roughly 25% — a result worth treating as one data point rather than a verdict, but a striking one for a freely licensed model.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| Kokoro | Chatterbox | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 94 | 92 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first data | Yes | Yes |
| License | Apache-2.0 | MIT |
| Pricing | Free — weights are Apache-2.0. Costs are hardware only; a rented GPU capable of faster-than-real-time synthesis runs roughly $20–$80/month, and nothing at all if you already own a suitable card. | Free — MIT licensed weights and code. Hardware only; a GPU is recommended for comfortable real-time cloning. |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | Well under 2 GB of VRAM on a GPU — Kokoro-FastAPI measured 758 MiB freed on unload after a short clip and 1,656 MiB after 7.5 minutes of long-form audio on an RTX 4060 Ti. On CPU, an ordinary laptop with a couple of GB free is enough (estimate; not stated at source). | About 5–6 GB of VRAM for the original 500M model — one user reports ~5 GB normally and 6 GB at peak on a GTX 1060 6 GB (GitHub issue #508). The project states no VRAM figure; Turbo (350M) is described as needing less. |
| Realistic running costWhat the box costs each month if you run it yourself. | $0 — it runs on the machine you already own | $0 on a PC with a 6 GB+ NVIDIA card you already own; otherwise a 24 GB RTX 3090/4090 on RunPod at $0.22–0.74/hr (read 2026-09-30) is more than enough |
| Setup timeHonest first-install estimate, not the marketing quickstart. | 15 minutes: pip install, install espeak-ng, generate a test clip | 30 minutes with pip on a working CUDA setup; longer on Windows, where the popular server wrapper pins Python 3.10 |
| Ongoing maintenanceThe part nobody budgets for. | Little to maintain, and little arriving: the hexgrad/kokoro repo was last pushed on 2025-08-06 and the v1.0 weights date from January 2025. Pin kokoro, misaki and torch versions so a dependency bump cannot change pronunciation. | Active: new variants (Turbo, Nano, Multilingual V3) keep arriving under new class names, so pin the package version. An open issue (#218) reports memory growing across generations on Apple Silicon — restart long-running workers on a schedule. |
Kokoro is Macrostack's recommended ElevenLabs alternative, so it's our pick here.
What will the GPU cost? Compare every company’s hourly price
Weighing both against staying on ElevenLabs? Is ElevenLabs free? What it actually costs →
Kokoro
Strengths
- +Apache-2.0 — commercial use with no restrictions
- +Tiny: ~300MB, runs faster than real time on modest hardware
- +Ranks top of the TTS Arena leaderboard despite its size
- +No per-character billing — cost stops scaling with usage
Trade-offs
- −No built-in voice cloning — you use the voices it ships with
- −Fewer languages than ElevenLabs' multilingual models
- −You own the deployment, updates, and uptime
Chatterbox
Strengths
- +MIT licence — the most permissive terms available here
- +Zero-shot voice cloning from about five seconds of audio
- +Emotion and intensity control, roughly 23 languages
- +Won a published blind preference test against ElevenLabs
Trade-offs
- −Heavier than Kokoro — wants a real GPU for smooth cloning
- −Voice cloning carries consent and likeness obligations that are yours to manage
- −Younger project, smaller ecosystem and less documentation
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose Kokoro
if a lower exit cost matters more to you than any single feature, and apache-2.0 — commercial use with no restrictions.
Choose Chatterbox
if mIT licence — the most permissive terms available here.
Neither, yet
if both carry a real cost you should weigh first — no built-in voice cloning — you use the voices it ships with, and heavier than Kokoro — wants a real GPU for smooth cloning. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
Self-hosting Kokoro
Well under 2 GB of VRAM on a GPU — Kokoro-FastAPI measured 758 MiB freed on unload after a short clip and 1,656 MiB after 7.5 minutes of long-form audio on an RTX 4060 Ti. On CPU, an ordinary laptop with a couple of GB free is enough (estimate; not stated at source). RAM · 15 minutes: pip install, install espeak-ng, generate a test clip
$0 — it runs on the machine you already own
Self-hosting Chatterbox
About 5–6 GB of VRAM for the original 500M model — one user reports ~5 GB normally and 6 GB at peak on a GTX 1060 6 GB (GitHub issue #508). The project states no VRAM figure; Turbo (350M) is described as needing less. RAM · 30 minutes with pip on a working CUDA setup; longer on Windows, where the popular server wrapper pins Python 3.10
$0 on a PC with a 6 GB+ NVIDIA card you already own; otherwise a 24 GB RTX 3090/4090 on RunPod at $0.22–0.74/hr (read 2026-09-30) is more than enough
Kokoro vs Chatterbox — common questions
Is Kokoro a better fit than Chatterbox for ai voice & speech?
It depends on what you are optimising for, and the honest split is this: Kokoro scores 94 to Chatterbox's 92 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Chatterbox earns its place on a different axis — mIT licence — the most permissive terms available here. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
Kokoro keeps its data local or in open formats, so leaving is an export rather than a negotiation. Chatterbox is still self-hostable, so the files stay on your server either way — but it is not local-first by design, so check what its export produces before you rely on it.
Can I self-host Kokoro or Chatterbox?
Both can be self-hosted. The difference is what it costs you in time rather than whether it is possible — see the setup and maintenance rows above.
Are Kokoro and Chatterbox both alternatives to ElevenLabs?
Yes — both appear in our ElevenLabs comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off ElevenLabs and now choosing between the two replacements, which is a narrower and much easier question.
More ElevenLabs head-to-heads
Related alternative guides
Facts verified 2026-07-29. Licenses and pricing change — spotted something out of date? That's a correction we want.