ElevenLabs • audioFeatured
Latest general-availability ElevenLabs speech model focused on expressive text-to-speech, multi-speaker control and production-grade voice output.
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Eleven v3 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio API Readiness | 95.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Composite | 94.2 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Control | 96.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Latency | 91.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Quality | 97.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SWEN Audio Value | 82.0 | 100.0 | SWEN Audio Registry v2026-06-22. Editorial multimodal ranking with modality-specific scoring based on product capability, control, speed, value and integration readiness. |
Eleven v3 is an AI model developed by ElevenLabs, classified as a audio model. It is a multimodal model, capable of processing text, images, and potentially other media types. As a proprietary model, it is available via ElevenLabs's cloud API.
Eleven v3 does not have public per-token pricing available at this time. Some models offer access via enterprise plans or research programs. Check ElevenLabs's official website for up-to-date availability and pricing.
Eleven v3 was evaluated on 6 different benchmarks, covering categories like API Readiness, audio, Control, Latency, Quality, Value. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Eleven v3 specializes in audio, offering advanced capabilities for creating and processing audio content.
In the 2026 AI model ecosystem, Eleven v3 competes directly with similarly capable models. ElevenLabs competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Latest general-availability ElevenLabs speech model focused on expressive text-to-speech, multi-speaker control and production-grade voice output.
Eleven v3 does not have public per-token pricing available at this time. Check ElevenLabs's official website for up-to-date information.
In available benchmarks, Eleven v3 scored: SWEN Audio API Readiness: 95/100, SWEN Audio Composite: 94.2/100, SWEN Audio Control: 96/100. See the full table above for a detailed comparison.
No, Eleven v3 is a proprietary model from ElevenLabs. It is available via cloud API. For open source alternatives, check our open source model ranking.
Eleven v3 excels at general-purpose language tasks.
Last updated: June 22, 2026 • View methodology →