ElevenLabs launched Eleven v4 and v4 Turbo on September 28, 2026, enhancing its text-to-speech capabilities with more emotive and low-latency models. The v4 model is ranked #1 by Artificial Analysis for expressiveness, while v4 Turbo boasts a median inference latency of ~100ms .
These new models represent a significant step forward in generating speech that mirrors human emotion and conversational flow. They address the long-standing challenge of creating AI voices that sound natural and responsive across various applications.
The introduction impacts fields from entertainment and audiobooks to customer service, enabling more engaging and realistic AI interactions. Both models are available via ElevenAgents, ElevenCreative, and ElevenAPI, broadening access for developers and creators.
What are the core capabilities of Eleven v4?
Eleven v4 is designed to interpret a wide range of vocal nuances, including tone, pacing, emotion, character, and context, making speech sound dramatic, tender, urgent, or conversational. It achieves this through an entirely new architecture, also improving multi-speaker dynamics for more responsive and realistic conversations.Users gain fine-grained control over outputs, allowing them to describe desired delivery in natural language. The model accurately follows inline tags for emotions and sound effects, like `[laughs]` or `[said angrily]`. Support for International Phonetic Alphabet (IPA) phonemes has also seen significant improvement for custom pronunciations.
The model preserves speaker identity consistently, crucial for long-form content such as audiobooks and agent conversations. This ensures characters and narrators maintain unique qualities throughout a production, even with regenerated lines or dialogue between multiple speakers.
How does voice cloning and multi-language support perform?
Eleven v4 enhances voice cloning with more authentic results and improved speaker similarity to the original source. Instant Voice Clones can now be generated from just 10 seconds of audio, maintaining high fidelity.The model also supports Professional Voice Clones (PVC) for the highest fidelity requirements. Both Eleven v4 and v4 Turbo support over 90 languages, allowing a voice recorded in one language to speak others fluently with native accent adherence, which prevents drift back to the source accent.
How does v4 Turbo address latency for real-time applications?
Eleven v4 Turbo combines speed and expressiveness for low-latency use cases, offering a median inference latency of ~100ms and a median time to first speech of ~150ms . This speed allows for deployment in real-time conversational agents, responding faster than typical human pauses.The v4 Turbo model is specifically optimized to work with ElevenLabs’ conversational agents platform, ElevenAgents. This integrated approach ensures more expressive, reliable, and low-latency agent interactions, supporting applications in healthcare, gaming, and customer support. For more on optimizing AI models, explore AI research and engineering skills.
Feature | Eleven v4 | Eleven v4 Turbo |
|---|---|---|
Primary Focus | Emotive speech generation | Low-latency, real-time applications |
Latency (Median Inference) | Standard | ~100ms |
Expressiveness | Highest | High (optimized for speed) |
Use Cases | Audiobooks, voiceovers, character performances | Conversational agents, interactive systems |
Multi-Language Support | 90+ languages | 90+ languages |
What does this mean for users?
Developers can create highly expressive and natural-sounding AI agents for diverse industries, from customer service to interactive gaming, leveraging the new models' emotional depth and low latency.
Content creators can produce more engaging audiobooks, character performances, and localized content with improved voice cloning and consistent speaker identities across multiple languages.
Businesses can deploy AI solutions that offer more personalized and human-like interactions, enhancing user experience and overcoming the 'monotone agent' problem often seen in earlier text-to-speech systems.
