Resemble AI Launches Chatterbox Turbo

Benchmarking Open-Source Voice AI with Transparent Evaluation

When Resemble AI open-sourced Chatterbox, it sent a clear signal to the Voice AI industry.
Open-source text-to-speech models were no longer experimental or niche. They were becoming viable alternatives to proprietary systems.

With the release of Chatterbox Turbo, Resemble AI takes that vision a step further.

Chatterbox Turbo is an MIT-licensed, open-source TTS model designed specifically for real-time voice applications, where latency, expressiveness, and trust are critical requirements rather than nice-to-haves.

What Makes Chatterbox Turbo Notable

Chatterbox Turbo focuses on performance characteristics that matter most in production voice systems.

It is built for real-time use cases and is claimed to match or outperform proprietary models such as ElevenLabs Turbo v2.5 in speed, quality, and expressiveness.

The model introduces paralinguistic prompting, enabling developers to control non-verbal cues such as pauses, hesitation, and expressive vocal behaviors. These details become essential when building conversational agents where even milliseconds impact user perception.

Chatterbox Turbo also produces expressive vocalizations, including natural umms and gasps, helping voice agents sound less scripted and more human.

For authentication-critical use cases, the model includes Resemble AI’s Perth watermarking by default. This ensures generated audio can be verified without additional tooling, addressing growing concerns around voice authenticity and misuse.

Chatterbox Turbo is publicly available via GitHub, Hugging Face, and Resemble AI’s website.

Why Evaluation Matters for Open-Source Voice AI

As open-source Voice AI models approach or exceed the performance of proprietary systems, evaluation becomes the differentiator.

Speed claims, expressiveness, and perceived naturalness cannot be validated by benchmarks alone. They require structured, human-centered evaluation that reflects how real listeners perceive voice quality.

To support the development and validation of Chatterbox Turbo, Resemble AI conducted evaluation using Podonos, benchmarking the model against both proprietary and open alternatives.

According to Zohaib, CEO of Resemble AI, building trustworthy Voice AI requires more than releasing powerful models. It requires transparent, reproducible evaluation that the broader community can inspect and learn from.

Public Benchmark Reports

The evaluation results are publicly available through Podonos report pages, allowing anyone to review model performance in a transparent and reproducible way.

Chatterbox Turbo vs ElevenLabs Turbo v2.5
https://podonos.com/resembleai/chatterbox-turbo-vs-elevenlabs-turbo

Chatterbox Turbo vs Cartesia Sonic 3
https://podonos.com/resembleai/chatterbox-turbo-vs-cartesia-sonic3

Chatterbox Turbo vs VibeVoice 7B
https://podonos.com/resembleai/chatterbox-turbo-vs-vibevoice7b

These evaluations reflect human perception across multiple dimensions, rather than relying solely on automated metrics.

A Signal for the Voice AI Ecosystem

Chatterbox Turbo represents more than a faster or more expressive TTS model.

It highlights a broader shift in the Voice AI ecosystem.
Open-source models are becoming production-ready, competitive, and credible. At the same time, transparent evaluation is becoming a foundational requirement, not an optional step.

At Podonos, we believe this combination of open development and rigorous evaluation is what enables Voice AI to scale responsibly.

Seeing open-source models benchmarked head-to-head with proprietary systems, with results shared publicly, is a meaningful step toward a more trustworthy and reproducible Voice AI future.