Index TTS 2.5

IndexTTS-2.5 is the open TTS model that finally gets the whole package in one node: zero-shot voice cloning, five languages, and controllable emotion. Most TTS in ComfyUI gives you "clone this voice, say this text." This one also lets you say "say it angry" - or feed it an 8-number emotion vector and watch the delivery change. That's the differentiator, and it's why you'd reach for it over the usual Kokoro or F5-TTS corners. Those are excellent, but they're mostly monotone-with-vibes; IndexTTS is a Chinese research release (IndexTeam) that shipped 2.5 with a big inference-speedup and multilingual expansion, and the community's standing verdict is that it clones well, with the caveat that it can read a little "robotic" next to the very best - the emotion control is what pulls it back into the genuinely useful column.

What it actually does

The node (IndexTTS2_5Node) takes your text plus a reference audio clip and produces a new clip of that voice saying your text, in zh, en, ja, es, or ar. Under the hood it's the official IndexTTS-2.5 stack vendored straight into the pack - autoregressive GPT backbone, a S2Mel acoustic stage, and the BigVGAN vocoder - so nothing extra to wire up. On first run it auto-downloads three auxiliary models (w2v-bert-2.0 semantic encoder, campplus_cn_common.bin speaker embedder, and bigvgan) into your models dir's hf_cache/. It also exports a subtitle string with rough >> timestamp lines if you want burned captions on a video.

The inputs that matter

The required set is small and you'll touch all of it:

• text - what to say (multiline).
• reference_audio - the voice to clone, as an AUDIO type, so load a clip with a video-loader node first. Quality here decides everything: loud, dynamic reference audio (podcast-style) clones far better than quiet, flat samples.
• language - zh / en / ja / es / ar.
• duration_factor - speaking speed, 0.5–2.0. This is your "faster/slower" knob.
• seed - set it to lock a take; note that 0 means not fixed, so zero won't give you reproducible results.

Emotion is optional and has three mutually exclusive routes: emo_ref_audio (a clip of the target emotion - ignored if the others are set), emo_vector (exactly 8 comma-separated or JSON numbers in the fixed order happy/angry/sad/afraid/disgusted/melancholic/surprised/calm - if you give anything but exactly 8, it's silently ignored, no error), and emo_text (describe it in words, like "angry", which a QwenEmotion model converts to the same vector - needs the optional qwen0.6bemo4-merge model). emo_alpha scales the whole thing 0–1. The sampling knobs (do_sample, temperature, top_p, top_k, repetition_penalty, num_beams, max_mel_tokens) are the standard LLM-generation family; leave them alone until you have a reason not to.

It returns three things: audio (AUDIO - wire to a preview or save node), seed, and subtitle.

Installing it

Grab it from ComfyUI Manager (search "IndexTTS"), or:

cd ComfyUI/custom_nodes
git clone https://github.com/mailzwj/ComfyUI-IndexTTS-2.5
cd ComfyUI-IndexTTS-2.5
pip install -r requirements.txt

Then drop the weights where the loader looks for them:

hf download IndexTeam/IndexTTS-2.5 --local-dir="<ComfyUI>/models/TTS/IndexTTS-2.5"

That's the whole pack: main node plus the Emo Settings helper. The dependency list is long and unsexy (librosa, sentencepiece, tiktoken, whisper, modelscope, wetext, …) but the author deliberately skipped the official keras==2.9.0 legacy dependency, so it doesn't force you onto an old Python. One real gotcha: the vendored indextts source is patched (compatibility_patch.py) to work with transformers 4.57.x. If your environment has a different transformers, expect it to break until the patch catches up. Japanese TTS additionally wants fugashi + unidic-lite, and flash-attn is off by default to dodge CUDA ABI mismatches.

Troubleshooting

• "IndexTTS-2.5 模型目录缺少文件" - models aren't in models/TTS/IndexTTS-2.5. Run the hf download command above.
• Weird errors right after install - almost certainly the transformers version vs. the compatibility patch. Check what's installed; that's the first thing to suspect.
• Slow HuggingFace downloads - set export HF_ENDPOINT="https://hf-mirror.com" before first run.
• Clones sound flat or warbly - swap the reference clip for something louder and more dynamic. Community testing on IndexTTS models found reference quality is the single biggest lever, by far. Output is also modest sample-rate mono (the earlier IndexTTS wrapper's users measured ~22kHz), so don't chase studio fidelity on the output side.

The one trap that'll waste an hour: forgetting emo_vector must be exactly 8 numbers. Nine, or a typo, and it's dropped with zero feedback - the synthesis just runs emotionless.