Top 10 Open Source Alternatives to ElevenLabs

CURATED LIST · 10 hand-picked projects · Updated August 23, 2026

Self-hosting voice generation requires matching model capabilities, licensing, and deployment requirements to your workload. The seven commercial choices rank by permissive licensing, active maintenance, self-hosting fit, deployment maturity, voice task fit, and operational constraints.

Flat illustration of a portable audio recorder with crossed microphones and ten blank plug-in voice cartridges or cards, one with a red waveform

Selection method

Rankings are driven by commercial licensing, active maintenance, self-hosting fit, deployment maturity, voice task fit, and operational constraints rather than GitHub stars.

Permissive commercial licensing

Code and model checkpoint license terms that permit commercial deployment.

Active maintenance

Repository activity, archived status, and community maintenance status.

Self-hosting fit

Feasibility of self-hosting on local CPU or GPU infrastructure.

Deployment maturity

Available execution paths such as ONNX runtime models or PyTorch setups.

Voice task fit

Match for zero-shot cloning, preset voice packs, or text voice descriptions.

Constraints

Clear accounting of watermarks, phonemizer dependencies, or non-commercial checkpoints.

The 10 ElevenLabs alternatives at a glance

Candidate	License	Status	Focus
#1 Chatterbox Resemble AI	MIT	Permissive MIT license (check watermark)	Reference-audio voice cloning in 23+ languages with PerTh watermarking
#2 Kokoro-82M hexgrad	Apache-2.0	Apache-2.0 licensed	Compact 82M parameter model with preset voice packs for CPU and ONNX
#3 OpenVoice V2 MyShell AI	MIT	Permissive MIT license	Instant voice cloning and style control across 6 official languages
#4 MeloTTS MyShell AI	MIT	Permissive MIT license	Compact, real-time oriented multilingual text-to-speech
#5 Parler-TTS Hugging Face	Apache-2.0	Apache-2.0 licensed	Voice characteristic control via natural-language text descriptions
#6 Piper Rhasspy / Community	MIT code / per-voice model cards	Inspect voice model licenses	Downloadable per-voice ONNX models for CPU and offline inference
#7 StyleTTS2 yl4579	MIT code / inspect weights	Inspect weights and runtime before shipping	Expressive English speech synthesis via style diffusion
#8 F5-TTS SWivid	Code MIT / Checkpoints CC-BY-NC-4.0	Non-commercial official checkpoints	Zero-shot EN/ZH voice cloning research model
#9 Coqui XTTS-v2 Coqui AI (Archived)	Code MPL-2.0 / Weights CPML (Non-Commercial)	Archived / Non-commercial weights	Multilingual voice cloning from short reference audio clips
#10 Fish Speech Fish Audio	Fish Audio Research License	Commercial agreement required	Multilingual and expressive voice generation research model

Detailed candidate reviews

Commercial short-list candidates

Candidates to evaluate for commercial self-hosting. Inspect each project's status badge and caveat for voice license or runtime requirements.

RANK #1

Chatterbox

Developed by Resemble AI

Permissive MIT license (check watermark) Not in AwesomeOSAI registry

Reference-audio voice cloning in 23+ languages with PerTh watermarking

Best for:Reference-audio voice cloning across multilingual deployments.

Grounded rationale:Resemble AI released Chatterbox under the MIT license, supporting zero-shot voice cloning from reference audio clips across 23+ languages. The Nano variant targets low-resource inference, while larger Chatterbox model checkpoints favor a GPU.

Caveats & limitations:Generated audio carries Resemble AI's PerTh watermark, and larger models favor a GPU.

Sources:Chatterbox repository•Chatterbox model card

Direct GitHub source →

RANK #2

Kokoro-82M

Developed by hexgrad

Apache-2.0 licensed Not in AwesomeOSAI registry

Compact 82M parameter model with preset voice packs for CPU and ONNX

Best for:Lightweight text-to-speech with preset voices on CPU or ONNX runtimes.

Grounded rationale:Kokoro-82M publishes its weights under Apache-2.0. Its v1.0 release added roughly eight languages and 54 voices. The 82M-parameter model has CPU and ONNX execution paths.

Caveats & limitations:Uses preset voice packs rather than arbitrary zero-shot voice cloning.

Sources:Kokoro source•Kokoro-82M model card

Direct GitHub source →

RANK #3

OpenVoice V2

Developed by MyShell AI

Permissive MIT license Not in AwesomeOSAI registry

Instant voice cloning and style control across 6 official languages

Best for:Instant voice cloning with style control in supported languages.

Grounded rationale:OpenVoice V2 is MIT-licensed and supports instant voice cloning and style control. Its official language list covers English, Spanish, French, Chinese, Japanese, and Korean.

Caveats & limitations:Requires setting up the speaker-encoder and style-converter pipeline components.

Sources:OpenVoice source•OpenVoice research

Direct GitHub source →

RANK #4

MeloTTS

Developed by MyShell AI

Permissive MIT license Not in AwesomeOSAI registry

Compact, real-time oriented multilingual text-to-speech

Best for:Compact multilingual synthesis covering English variants and international languages.

Grounded rationale:MeloTTS is MIT-licensed and supports English variants, Spanish, French, Chinese, Japanese, and Korean. It is a compact, real-time oriented choice.

Caveats & limitations:Does not center zero-shot voice cloning.

Sources:MeloTTS source

Direct GitHub source →

RANK #5

Parler-TTS

Developed by Hugging Face

Apache-2.0 licensed Not in AwesomeOSAI registry

Voice characteristic control via natural-language text descriptions

Best for:Controlling voice characteristics through text descriptions.

Grounded rationale:Parler-TTS releases code and checkpoints under Apache-2.0. It steers voice characteristics through a natural-language description rather than cloning an arbitrary speaker clip.

Caveats & limitations:Parler-TTS Mini is substantially heavier than Piper or Kokoro and typically favors a GPU.

Sources:Parler-TTS source•Parler-TTS paper

Direct GitHub source →

RANK #6

Piper

Developed by Rhasspy / Community

Inspect voice model licenses Not in AwesomeOSAI registry

Downloadable per-voice ONNX models for CPU and offline inference

Best for:Offline CPU inference using per-voice ONNX models.

Grounded rationale:Piper uses ONNX Runtime and ships downloadable, per-voice ONNX models for local synthesis.

Caveats & limitations:The original Rhasspy repository is archived. Current alternatives and individual voice model cards need separate maintenance and license checks. Piper does not do instant voice cloning.

Sources:Piper source•Piper voices

Direct GitHub source →

RANK #7

StyleTTS2

Developed by yl4579

Inspect weights and runtime before shipping Not in AwesomeOSAI registry

Expressive English speech synthesis via style diffusion

Best for:Expressive English speech generation requiring PyTorch GPU setups.

Grounded rationale:StyleTTS2 code is MIT-licensed and uses style diffusion for expressive English speech synthesis.

Caveats & limitations:Original released examples focus on English, and running the original repository needs a GPU-oriented PyTorch setup plus phonemizer dependencies.

Sources:StyleTTS2 source•StyleTTS2 paper

Direct GitHub source →

Research and evaluation references, not commercial replacements

Restricted checkpoints or custom licenses that block direct commercial use.

REFERENCE #8

F5-TTS

Developed by SWivid

Non-commercial official checkpoints Not in AwesomeOSAI registry

Zero-shot EN/ZH voice cloning research model

Best for:Academic research and non-commercial zero-shot evaluation.

Grounded rationale:F5-TTS code is MIT, but its official Emilia-trained checkpoints are CC-BY-NC-4.0. The project is good at zero-shot EN/ZH voice cloning.

Licensing restriction & caveats:Published models are a poor fit for commercial use unless the team trains its own permissively sourced checkpoint.

Sources:F5-TTS source and licensing note•F5-TTS paper

Direct GitHub source →

REFERENCE #9

Coqui XTTS-v2

Developed by Coqui AI (Archived)

Archived / Non-commercial weights Not in AwesomeOSAI registry

Multilingual voice cloning from short reference audio clips

Best for:Historical benchmark evaluation across 17 languages.

Grounded rationale:Coqui XTTS-v2 supports 17 languages and describes cloning from a short reference clip.

Licensing restriction & caveats:TTS code is MPL-2.0, but XTTS-v2 weights use the non-commercial Coqui Public Model License. The original project was archived after Coqui's shutdown, so it is not an actively maintained commercial option.

Sources:XTTS-v2 model card•Coqui TTS source

Direct GitHub source →

REFERENCE #10

Fish Speech

Developed by Fish Audio

Commercial agreement required Not in AwesomeOSAI registry

Multilingual and expressive voice generation research model

Best for:Non-commercial research on expressive multilingual audio.

Grounded rationale:Fish Speech has strong multilingual and expressive generation capabilities.

Licensing restriction & caveats:The Fish Audio Research License requires a separate agreement for commercial use. It does not meet a strict open-source commercial-replacement test.

Sources:Fish Speech source

Direct GitHub source →

Decision guide

Requirement	Recommendation	Why
Instant voice cloning under a commercial license	Chatterbox (MIT) or OpenVoice V2 (MIT)	Chatterbox supports reference audio cloning in 23+ languages with a PerTh watermark; OpenVoice V2 supports instant cloning and style control across six languages.
Preset voices on CPU or ONNX	Kokoro-82M (Apache-2.0)	Kokoro-82M offers an 82M model with 54 voices and CPU/ONNX paths.
Prompting voice characteristics in plain text	Parler-TTS (Apache-2.0)	Parler-TTS steers voice traits through text descriptions rather than speaker cloning clips.
Compact multilingual CPU text-to-speech	MeloTTS (MIT)	MeloTTS supports English variants, Spanish, French, Chinese, Japanese, and Korean.
Offline per-voice ONNX models	Piper (ONNX / audit voice cards)	Piper ships per-voice ONNX models, though the original repository is archived and individual voice model cards require license checks.
Expressive English PyTorch GPU generation	StyleTTS2 (MIT code / inspect weights)	StyleTTS2 uses style diffusion for English speech, requiring PyTorch, GPU hardware, and phonemizer dependencies.
Non-commercial zero-shot evaluation	F5-TTS, XTTS-v2, or Fish Speech	Useful for research, but official weights require custom commercial licensing or clean weight retraining.

Questions people ask

Can Kokoro-82M do instant voice cloning from a user audio clip?

No. Kokoro-82M uses preset voice packs (54 voices in v1.0) rather than arbitrary zero-shot voice cloning. For instant voice cloning from reference audio clips under an open license, evaluate Chatterbox or OpenVoice V2.

Does Chatterbox require a GPU?

Not for all workloads. Chatterbox Nano targets low-resource inference, while larger Chatterbox model checkpoints favor a GPU. Generated audio carries Resemble AI's PerTh watermark.

Why are F5-TTS, XTTS-v2, and Fish Speech kept off the commercial short-list?

Official F5-TTS Emilia checkpoints carry CC-BY-NC-4.0, XTTS-v2 weights use the non-commercial Coqui Public Model License (and its repository is archived), and Fish Speech requires a separate commercial agreement under its research license. None of the three provide a clear commercial replacement out of the box.

What should I check before deploying Piper or StyleTTS2?

Piper code is MIT and uses ONNX Runtime, but the original Rhasspy repository is archived and individual voice models require separate license audits. StyleTTS2 code is MIT, but running it requires a PyTorch GPU setup with phonemizer dependencies, and model weight terms must be inspected before deployment.

Sources

Related internal pages

Related self-hosted guides and alternative pages:

Official Weekly Digest

Stay Updated on Open-Source AI

Get net-new open-source models, agent frameworks, inference engines, and tools delivered directly to your inbox every week.

The AwesomeOSAI registry currently has no active standalone project record for any of the ten candidates. GitHub and model card links are provided directly above.