What are Voice Cloning Models for Edge Deployment?
Voice cloning models for edge deployment are specialized text-to-speech (TTS) AI models optimized to run efficiently on resource-constrained devices such as smartphones, IoT devices, and embedded systems. These models leverage advanced architectures like autoregressive transformers and finite scalar quantization to deliver high-quality, natural-sounding speech synthesis with minimal latency and computational overhead. They enable zero-shot voice cloning, allowing users to replicate any voice from short audio samples without extensive training. This technology democratizes access to professional voice synthesis, enabling applications in real-time communication, assistive technology, content creation, and multilingual voice interfaces—all while maintaining privacy and performance on edge devices.
FunAudioLLM/CosyVoice2-0.5B
CosyVoice 2 is a streaming speech synthesis model based on a large language model, employing a unified streaming/non-streaming framework design. The model enhances the utilization of the speech token codebook through finite scalar quantization (FSQ), simplifies the text-to-speech language model architecture, and develops a chunk-aware causal streaming matching model that supports different synthesis scenarios. In streaming mode, the model achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to that of non-streaming mode.
FunAudioLLM/CosyVoice2-0.5B: Ultra-Low Latency Streaming Voice Synthesis
CosyVoice 2 is a streaming speech synthesis model based on a large language model, employing a unified streaming/non-streaming framework design. The model enhances the utilization of the speech token codebook through finite scalar quantization (FSQ), simplifies the text-to-speech language model architecture, and develops a chunk-aware causal streaming matching model that supports different synthesis scenarios. In streaming mode, the model achieves ultra-low latency of 150ms while maintaining synthesis quality almost identical to that of non-streaming mode. Compared to version 1.0, the pronunciation error rate has been reduced by 30%-50%, the MOS score has improved from 5.4 to 5.53, and fine-grained control over emotions and dialects is supported. The model supports Chinese (including dialects: Cantonese, Sichuan dialect, Shanghainese, Tianjin dialect, etc.), English, Japanese, Korean, and supports cross-lingual and mixed-language scenarios.
Pros
- Ultra-low latency of 150ms in streaming mode, ideal for edge deployment.
- Compact 0.5B parameter model optimized for resource-constrained devices.
- 30%-50% reduction in pronunciation error rate compared to v1.0.
Cons
- Smaller model size may limit some advanced voice customization features.
- Dialect support primarily focused on Chinese variants.
Why We Love It
- It delivers real-time, high-quality voice synthesis with 150ms latency, making it the perfect choice for edge deployment scenarios requiring instant response and minimal computational resources.
fishaudio/fish-speech-1.5
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model. The model employs an innovative DualAR architecture, featuring a dual autoregressive transformer design. It supports multiple languages, with over 300,000 hours of training data for both English and Chinese, and over 100,000 hours for Japanese. In independent evaluations by TTS Arena, the model performed exceptionally well, with an ELO score of 1339.
fishaudio/fish-speech-1.5: Top-Ranked Multilingual Voice Cloning
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model. The model employs an innovative DualAR architecture, featuring a dual autoregressive transformer design. It supports multiple languages, with over 300,000 hours of training data for both English and Chinese, and over 100,000 hours for Japanese. In independent evaluations by TTS Arena, the model performed exceptionally well, with an ELO score of 1339. The model achieved a word error rate (WER) of 3.5% and a character error rate (CER) of 1.2% for English, and a CER of 1.3% for Chinese characters. This exceptional accuracy combined with extensive multilingual training makes it ideal for edge deployment in global voice cloning applications.
Pros
- Top-ranked performance with ELO score of 1339 on TTS Arena.
- Innovative DualAR dual autoregressive transformer architecture.
- Extensive training: 300,000+ hours for English and Chinese.
Cons
- Larger model size may require optimization for some edge devices.
- Higher pricing at $15/M UTF-8 bytes on SiliconFlow compared to alternatives.
Why We Love It
- It combines benchmark-leading accuracy with robust multilingual capabilities and an innovative dual transformer architecture, making it the gold standard for high-quality voice cloning on edge devices.
IndexTeam/IndexTTS-2
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech (TTS) model designed to address the challenge of precise duration control in large-scale TTS systems. It introduces a novel method for speech duration control, supporting two modes: one that explicitly specifies the number of generated tokens for precise duration, and another that generates speech freely in an auto-regressive manner.
IndexTeam/IndexTTS-2: Zero-Shot Voice Cloning with Precise Duration Control
IndexTTS2 is a breakthrough auto-regressive zero-shot Text-to-Speech (TTS) model designed to address the challenge of precise duration control in large-scale TTS systems, which is a significant limitation in applications like video dubbing. It introduces a novel, general method for speech duration control, supporting two modes: one that explicitly specifies the number of generated tokens for precise duration, and another that generates speech freely in an auto-regressive manner. Furthermore, IndexTTS2 achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts. To enhance speech clarity in highly emotional expressions, the model incorporates GPT latent representations and utilizes a novel three-stage training paradigm. To lower the barrier for emotional control, it also features a soft instruction mechanism based on text descriptions, developed by fine-tuning Qwen3, to effectively guide the generation of speech with the desired emotional tone. Experimental results show that IndexTTS2 outperforms state-of-the-art zero-shot TTS models in word error rate, speaker similarity, and emotional fidelity across multiple datasets.
Pros
- Zero-shot voice cloning without requiring extensive training data.
- Precise duration control for applications like video dubbing.
- Independent control of timbre and emotion via separate prompts.
Cons
- May require more sophisticated prompting for optimal emotional control.
- Auto-regressive approach can be slower than streaming models for real-time applications.
Why We Love It
- It revolutionizes voice cloning with zero-shot capability and unprecedented control over duration, emotion, and timbre—perfect for edge deployment in professional dubbing, content creation, and interactive voice applications.
Voice Cloning Model Comparison
In this table, we compare 2026's leading voice cloning models optimized for edge deployment, each with a unique strength. For ultra-low latency streaming, FunAudioLLM/CosyVoice2-0.5B provides exceptional efficiency. For benchmark-leading multilingual accuracy, fishaudio/fish-speech-1.5 offers unmatched quality, while IndexTeam/IndexTTS-2 prioritizes zero-shot voice cloning with precise duration and emotional control. This side-by-side view helps you choose the right tool for your specific edge deployment scenario.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | FunAudioLLM/CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | 150ms ultra-low latency streaming |
| 2 | fishaudio/fish-speech-1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Top-ranked accuracy (ELO 1339) |
| 3 | IndexTeam/IndexTTS-2 | IndexTeam | Audio/Text-to-Speech | $7.15/M UTF-8 bytes | Zero-shot with duration control |
Frequently Asked Questions
Our top three picks for 2026 are FunAudioLLM/CosyVoice2-0.5B, fishaudio/fish-speech-1.5, and IndexTeam/IndexTTS-2. Each of these models stood out for their innovation, edge deployment optimization, and unique approach to solving challenges in real-time voice cloning, multilingual synthesis, and precise emotional control.
Our in-depth analysis shows FunAudioLLM/CosyVoice2-0.5B is the top choice for real-time edge deployment, achieving ultra-low latency of 150ms in streaming mode with a compact 0.5B parameter footprint. For applications requiring the highest accuracy and multilingual support, fishaudio/fish-speech-1.5 leads with its ELO score of 1339. For zero-shot voice cloning with precise duration and emotional control, IndexTeam/IndexTTS-2 is the optimal solution.