Resource workflow

Listen, decide, then test with your own material

Each resource has one job. Start with attributed examples, understand the model differences, then run a controlled comparison with your own authorized reference.

01 · Listen

Samples

Hear attributed official reference and showcase examples across supported languages.

02 · Decide

Model comparison

Compare hosted capabilities, upstream evidence, limitations, and model-selection guidance.

03 · Test

Voice Lab

Use your own authorized reference and script for a controlled IndexTTS2 vs 2.5 test.

Model comparison

IndexTTS2 vs IndexTTS 2.5: features, controls, and reference examples

IndexTTS2 and IndexTTS 2.5 are both available on IndexTTS Online, but they fit different needs. Compare the controls exposed here, supported target languages, and official IndexTeam reference examples before choosing a model.

Hosted capability comparison

These rows describe controls currently exposed by IndexTTS Online. They are product capabilities, not subjective quality scores.

Capability	IndexTTS2	IndexTTS 2.5
Hosted on IndexTTS Online	Yes	Yes
Target languages exposed here	Chinese, English	Chinese, English, Japanese, Spanish, Arabic
Explicit language selector	No	Yes
Emotion presets	Natural, Happy, Sad, Angry, Calm	Natural, Happy, Sad, Angry, Calm
Pace control exposed here	No	Faster, Normal, Slower

Product guidance

Which model should you use?

Choose IndexTTS2 when your target text is English or Chinese and you want the simpler hosted model path with the same core voice-cloning workflow.

Choose IndexTTS 2.5 when you need Japanese, Spanish, or Arabic target text, an explicit language selector, or pace controls in addition to the shared emotion presets.

If both models fit your language, use the same reference and target text in Voice Lab and choose the result that works better for your use case.

Open Voice Lab →Browse more samples →

Upstream evidence

What the IndexTTS 2.5 technical report says

The upstream IndexTTS 2.5 Technical Report reports a 2.28× improvement in real-time factor while maintaining comparable word error rate and speaker similarity to IndexTTS2. It also describes broader multilingual coverage and architectural changes intended to reduce inference cost.

This is an upstream published result, not a measurement produced by IndexTTS Online. Hardware, runtime, prompts, and serving infrastructure can change observed latency.

Read the technical report ↗Hear upstream 2.5 examples ↗

How to make a fair side-by-side comparison

01
Use the same reference voice
Keeping the speaker reference identical makes it easier to hear model differences instead of recording differences.
02
Use the same target text
The same wording and punctuation gives both models the same speaking task.
03
Change one control at a time
When comparing emotion or pace, avoid changing several settings at once.
04
Listen for practical differences
Focus on pronunciation, speaker similarity, prosody, stability, and audible artifacts for your own use case.

Official references

English and Chinese examples from the IndexTeam demo

English and Chinese are useful side-by-side reference languages because both hosted models support them. The audio below comes from the official IndexTeam example corpus and remains clearly attributed to its upstream source.

Source note: the reference recordings above are upstream IndexTeam demo assets. IndexTTS Online provides comparison context and hosted tools but does not claim ownership of those recordings.

Browse more samples →Open Voice Lab →Upstream example cases ↗

Practical guides

Learn the workflow behind the tool

Use focused guides to improve reference audio, choose models, prepare scripts, and compare results under controlled conditions.

6 min read

IndexTTS2 vs IndexTTS 2.5: Which Model Should You Use?

A practical comparison of IndexTTS2 and IndexTTS 2.5 based on language coverage, controls, workflow needs, and production trade-offs.

Read guide

9 min read

A Reproducible A/B Testing Method for AI Voice Cloning

Compare voice-cloning models, references, scripts, emotion, or pace with controlled inputs, useful listening criteria, repeat runs, and honest reporting without fabricated MOS.

Read guide

6 min read

AI Voice Quality Checklist: How to Review Cloned Speech Before You Publish

A practical review checklist for identity, pronunciation, pacing, artifacts, consent, disclosure, and final publication quality.

Read guide

Browse all guides

Resource workflow

Listen, decide, then test with your own material

Each resource has one job. Start with attributed examples, understand the model differences, then run a controlled comparison with your own authorized reference.

01 · Listen

Samples

Hear attributed official reference and showcase examples across supported languages.

02 · Decide

Model comparison

Compare hosted capabilities, upstream evidence, limitations, and model-selection guidance.

03 · Test

Voice Lab

Use your own authorized reference and script for a controlled IndexTTS2 vs 2.5 test.

Hosted capability comparison

These rows describe controls currently exposed by IndexTTS Online. They are product capabilities, not subjective quality scores.

Capability	IndexTTS2	IndexTTS 2.5
Hosted on IndexTTS Online	Yes	Yes
Target languages exposed here	Chinese, English	Chinese, English, Japanese, Spanish, Arabic
Explicit language selector	No	Yes
Emotion presets	Natural, Happy, Sad, Angry, Calm	Natural, Happy, Sad, Angry, Calm
Pace control exposed here	No	Faster, Normal, Slower

Which model should you use?

Choose IndexTTS2 when your target text is English or Chinese and you want the simpler hosted model path with the same core voice-cloning workflow.

Choose IndexTTS 2.5 when you need Japanese, Spanish, or Arabic target text, an explicit language selector, or pace controls in addition to the shared emotion presets.

If both models fit your language, use the same reference and target text in Voice Lab and choose the result that works better for your use case.

What the IndexTTS 2.5 technical report says

This is an upstream published result, not a measurement produced by IndexTTS Online. Hardware, runtime, prompts, and serving infrastructure can change observed latency.

How to make a fair side-by-side comparison

Use the same reference voice

Keeping the speaker reference identical makes it easier to hear model differences instead of recording differences.

Use the same target text

The same wording and punctuation gives both models the same speaking task.

Change one control at a time

When comparing emotion or pace, avoid changing several settings at once.

Listen for practical differences

Focus on pronunciation, speaker similarity, prosody, stability, and audible artifacts for your own use case.

English and Chinese examples from the IndexTeam demo

Source note: the reference recordings above are upstream IndexTeam demo assets. IndexTTS Online provides comparison context and hosted tools but does not claim ownership of those recordings.