ElevenLabs
Hyper-realistic AI voice and speech synthesis
ElevenLabs is the leading AI voice platform, offering text-to-speech and voice cloning APIs. Its multilingual v2 model supports 29 languages with near-human quality, and Flash v2.5 delivers ultra-low latency for real-time voice applications.
ElevenLabs Flash v2.5 delivers sub-300ms latency for real-time voice applications, making it the go-to choice for voice AI agents.
- Best-in-class voice quality
- Ultra-low latency (Flash model)
- 29-language support
- Voice/TTS only — no text generation
- Per-character pricing can add up at scale
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Full comparison tableElevenLabs LLM pricing overview
ElevenLabs is a proprietary AI lab that develops and hosts its own large language models. ElevenLabs is the leading AI voice platform, offering text-to-speech and voice cloning APIs. Its multilingual v2 model supports 29 languages with near-human quality, and Flash v2.5 delivers ultra-low latency for real-time voice applications. Common use cases include Text-to-speech, Voice cloning, Audiobook generation, Real-time voice agents. Headquartered in New York, NY, founded 2022. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
ElevenLabs vs other LLM providers
ElevenLabs competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. ElevenLabs Flash v2.5 delivers sub-300ms latency for real-time voice applications, making it the go-to choice for voice AI agents. Use the LLM provider comparison tool to see ElevenLabs token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose ElevenLabs?
ElevenLabs's key strengths are: Best-in-class voice quality; Ultra-low latency (Flash model); 29-language support. Limitations to consider: Voice/TTS only — no text generation; Per-character pricing can add up at scale. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding ElevenLabs token pricing
ElevenLabs charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. Prices shown are sourced from ElevenLabs's public pricing page and updated daily. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
ElevenLabs context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when ElevenLabs makes sense
Managed inference APIs like ElevenLabs eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at ElevenLabs API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical ElevenLabs token price data is available in the LLM price history charts.