4 Best IndexTTS-2.5 Alternatives in 2026 (Open Source)
IndexTTS-2.5 — An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System. vs F5-TTS/CosyVoice: First autoregressive TTS model with precise duration control for video dubbing, plus emotion-timbre disentanglement allowing independent control of voice identity and emotional expression - developed by Bilibili
These 4 open-source tools do the same job. They are ordered by how closely they match IndexTTS-2.5, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| IndexTTS-2.5(original) | 24.2k | +740 | 2026-09-29 |
| ChatTTS | 39.9k | +142 | 2026-04-10 |
| EmotiVoice | 8.5k | +12 | 2026-09-03 |
| TTS-WebUI | 3.3k | +39 | 2026-09-07 |
| AudioGPT | 10.2k | +-7 | 2023-05-05 |
1. ChatTTS
A generative speech model for daily dialogue.
What sets it apart: Purpose-built for dialogue TTS with fine-grained control over prosody (laughter, pauses, interjections) that most TTS models lack — trained on 100K+ hours, with multi-speaker and streaming support, but deliberately limited for safety
Best for: Research on conversational TTS with prosodic control; Building dialogue-oriented voice interfaces (non-commercial); Chinese language TTS applications
2. EmotiVoice
EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine
What sets it apart: vs standard TTS engines: prompt-controlled emotional synthesis across 2000+ voices — the ability to specify emotion (happy, sad, angry) alongside text sets it apart from monotone alternatives
Best for: Multilingual content creation requiring emotional nuance; Voice cloning applications with custom datasets; Applications needing diverse voice options with emotional variation
3. TTS-WebUI
A single Gradio + React WebUI with extensions for ACE-Step, Kimi Audio, Piper TTS, GPT-SoVITS, CosyVoice, XTTSv2, DIA, Kokoro, OpenVoice, ParlerTTS, Stable Audio, MMS, StyleTTS2, MAGNet, AudioGen, Mus
What sets it apart: vs individual TTS tools: Single unified interface supporting 25+ TTS/audio models with extension system, eliminating the need to set up separate environments for each model
Best for: Experimenting with and comparing multiple TTS models in one interface; Audio content creation workflows (voice, music, effects)
4. AudioGPT
AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head
What sets it apart: vs ElevenLabs / Bark / MusicGen: unified agent orchestrating 15+ specialized audio foundation models across speech, music, sound, and video — one interface for the entire audio AI landscape
Best for: Multi-modal audio research spanning speech, music, and sound; Prototyping audio AI pipelines with diverse foundation models; Accessibility applications combining speech and visual generation