What are Small Text-to-Speech Models?
Small text-to-speech models are compact AI systems specialized in converting written text into natural-sounding speech with minimal computational requirements. Using efficient deep learning architectures, they generate high-quality voice output while maintaining low latency and resource usage. This technology allows developers and creators to integrate voice synthesis into applications with unprecedented ease and affordability. They foster innovation, accelerate deployment, and democratize access to powerful speech synthesis tools, enabling a wide range of applications from virtual assistants to accessibility solutions and content creation.
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). 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.
FunAudioLLM/CosyVoice2-0.5B: Ultra-Low Latency Streaming TTS
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. At only 0.5B parameters, it delivers exceptional efficiency for real-time applications. Pricing on SiliconFlow: $7.15/M UTF-8 bytes.
Pros
- Ultra-low latency of 150ms in streaming mode.
- 30%-50% reduction in pronunciation error rate.
- Improved MOS score from 5.4 to 5.53.
Cons
- May require fine-tuning for specific use cases.
- Emotion control complexity may have a learning curve.
Why We Love It
- It delivers real-time, high-quality speech synthesis with ultra-low latency while supporting multiple languages and dialects—all in a compact 0.5B parameter package perfect for resource-constrained deployments.
fishaudio/fish-speech-1.5
Fish Speech V1.5 is a leading open-source text-to-speech (TTS) model employing an innovative DualAR architecture with 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 TTS
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 combination of extensive training data and innovative architecture makes it one of the most reliable small TTS models available. Pricing on SiliconFlow: $15/M UTF-8 bytes.
Pros
- Top-ranked with ELO score of 1339 in TTS Arena.
- Innovative DualAR architecture for superior quality.
- Over 300,000 hours of English and Chinese training data.
Cons
- Higher pricing compared to other small models.
- May require more computational resources than ultra-compact alternatives.
Why We Love It
- It's the top-ranked open-source TTS model with exceptional accuracy across multiple languages, backed by massive training data and an innovative dual autoregressive architecture.
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 supports two modes: one that explicitly specifies the number of generated tokens for precise duration, and another that generates speech freely. The model achieves disentanglement between emotional expression and speaker identity, enabling independent control over timbre and emotion via separate prompts.
IndexTeam/IndexTTS-2: Precise Duration Control & Zero-Shot Excellence
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. Pricing on SiliconFlow: $7.15/M UTF-8 bytes for both input and output.
Pros
- Precise duration control for video dubbing applications.
- Zero-shot voice cloning without additional training.
- Independent control of timbre and emotion.
Cons
- More complex configuration for advanced features.
- May require understanding of dual-mode operation.
Why We Love It
- It revolutionizes TTS with precise duration control and zero-shot capabilities, perfect for video dubbing and applications requiring independent control of emotion and voice characteristics.
TTS Model Comparison
In this table, we compare 2025's leading small text-to-speech models, each with a unique strength. For ultra-low latency streaming, FunAudioLLM/CosyVoice2-0.5B delivers exceptional real-time performance. For top-ranked multilingual quality, fishaudio/fish-speech-1.5 offers industry-leading accuracy. For precise duration control and zero-shot voice cloning, IndexTeam/IndexTTS-2 provides breakthrough capabilities. This side-by-side view helps you choose the right tool for your specific speech synthesis goal.
| Number | Model | Developer | Model Type | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | FunAudioLLM/CosyVoice2-0.5B | FunAudioLLM | Text-to-Speech | $7.15/M UTF-8 bytes | Ultra-low 150ms latency |
| 2 | fishaudio/fish-speech-1.5 | fishaudio | Text-to-Speech | $15/M UTF-8 bytes | Top-ranked ELO 1339 |
| 3 | IndexTeam/IndexTTS-2 | IndexTeam | Text-to-Speech | $7.15/M UTF-8 bytes | Precise duration control |
Frequently Asked Questions
Our top three picks for 2025 are FunAudioLLM/CosyVoice2-0.5B, fishaudio/fish-speech-1.5, and IndexTeam/IndexTTS-2. Each of these models stood out for their innovation, efficiency, and unique approach to solving challenges in text-to-speech synthesis while maintaining small model sizes suitable for real-world deployment.
Our in-depth analysis shows several leaders for different needs. FunAudioLLM/CosyVoice2-0.5B is the top choice for real-time streaming applications requiring ultra-low latency. For creators who need the highest quality multilingual synthesis with proven benchmark performance, fishaudio/fish-speech-1.5 is the best option. For video dubbing and applications requiring precise duration control and zero-shot voice cloning, IndexTeam/IndexTTS-2 excels with its breakthrough capabilities.