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0.46B parameters
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Reviewed May 2026

XTTS v2

Coqui's flagship multilingual voice-cloning TTS — clones a speaker from a 6-second reference clip and synthesizes in 17 languages with cross-lingual transfer. Released under the Coqui Public Model License (CPML), which restricts commercial use without a separate license.

License: Coqui Public Model License·Context: 0 tokens
BLK · VERDICT

Our verdict

OP · Fredoline Eruo|VERIFIED MAY 29, 2026
unrated

Technically excellent, legally radioactive for product use. If you need cloning + multilingual and can negotiate CPML, fine; otherwise look at F5-TTS or Orpheus.

Overview

Coqui's flagship multilingual voice-cloning TTS — clones a speaker from a 6-second reference clip and synthesizes in 17 languages with cross-lingual transfer. Released under the Coqui Public Model License (CPML), which restricts commercial use without a separate license.

Strengths

  • Few-shot voice cloning from ~6 seconds of reference audio
  • 17-language coverage with cross-lingual voice transfer
  • Strong expressivity and prosody compared to Piper/Kokoro
  • Massive community adoption — 9M+ downloads, mature tooling

Weaknesses

  • Coqui Public Model License explicitly forbids commercial use without a paid license — a real trap many users miss
  • Coqui the company shut down in early 2024, so upstream support is community-only
  • Higher latency than Kokoro/Piper; needs GPU for realtime
  • Clone quality varies sharply with reference audio cleanliness

Quantization variants

Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.

QuantizationFile sizeVRAM required
Q4_K_M0.3 GB1 GB

Get the model

HuggingFace

Original weights

huggingface.co/coqui/XTTS-v2

Source repository — direct quantization required.

Hardware that runs this

Cards with enough VRAM for at least one quantization of XTTS v2.

NVIDIA GB200 NVL72
13824GB · nvidia
AMD Instinct MI350X
288GB · amd
NVIDIA B300 (Blackwell Ultra)
288GB · nvidia
AMD Instinct MI355X
288GB · amd
AMD Instinct MI325X
256GB · amd
AMD Instinct MI300X
192GB · amd
NVIDIA B200
192GB · nvidia
NVIDIA H100 NVL
188GB · nvidia
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Frequently asked

What's the minimum VRAM to run XTTS v2?

1GB of VRAM is enough to run XTTS v2 at the Q4_K_M quantization (file size 0.3 GB). Higher-quality quantizations need more.

Can I use XTTS v2 commercially?

XTTS v2 is released under the Coqui Public Model License, which has restrictions for commercial use. Review the license terms before using it in a product.

What's the context length of XTTS v2?

XTTS v2 supports a context window of 0 tokens (about 0K).

Source: huggingface.co/coqui/XTTS-v2

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.

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Before you buy

Verify XTTS v2 runs on your specific hardware before committing money.

Will it run on my hardware? →Custom hardware comparison →GPU recommender (4 questions) →