Introducing Bland Speech v3, the most realistic voice model.

Looking for an ElevenLabs alternative?

Bland is a phone-native voice AI platform. ElevenLabs is a voice synthesis company expanding into agents.

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Bland and ElevenLabs both deliver excellent voices. The real difference is the platform: Bland runs the entire stack with no third-party LLM, which means lower latency, higher uptime, and stronger data governance for regulated teams. Bland is built only for phone agents and handles the most complex inbound calls, the ones that run dozens of minutes. ElevenLabs is a voice-model company whose agents product is newer and routes reasoning through a third-party LLM.

What teams run into with ElevenLabs

Reasoning runs on a third-party model

ElevenLabs Agents is bring-your-own-LLM, so every call routes its reasoning, and your data, through OpenAI, Anthropic, or Google. That is one more provider to vet and one more place regulated data lives. Bland runs its own models end to end, with no third party in the stack.

Agents are a new, secondary product

ElevenLabs is a voice-model company. The agents product arrived in 2025 and remains a small part of the business, so the depth that complex phone work demands is still forming.

Built for short synthesis, not the hard calls

The ElevenLabs strength is high-quality voice for media and short interactions. Bland is built for the multi-step inbound calls that run dozens of minutes and have to actually resolve.

Why teams switch to Bland

The whole stack, no third-party LLM

Bland runs its own models end to end. No call hands your data to OpenAI, Anthropic, or any third-party lab model, which means lower latency, higher uptime, a tighter security posture, and data governance regulated teams can sign off on.

Agents are the whole company

Bland does one thing: enterprise phone agents, proven on the most complex inbound calls that run dozens of minutes. ElevenLabs added agents in 2025 as a secondary line on top of a voice-model business.

Voices on par, agents more robust

Bland voices stand with the best in the industry. The difference is everything around the voice: reasoning, tools, reliability, and handling the calls that do not fit a script.

Bland vs ElevenLabs, line by line

FeatureBlandElevenLabs
Core focusEnterprise phone agents, the entire companyVoice models; agents are a newer, secondary product
The stackFull proprietary stack, no third-party LLMBring-your-own-LLM (OpenAI, Anthropic, Google)
Voice qualityOn par with the bestIndustry-leading synthesis
Best forThe most complex inbound calls, dozens of minutes longBest on shorter, simpler interactions
Data governanceData never leaves the stack for a third-party modelReasoning and data pass through your LLM provider
ComplianceSOC 2 Type II, HIPAA, PCI DSS, GDPRSOC 2 Type II, HIPAA, GDPR, ISO 27001
Pricing$0.09 to $0.14/min, all-inclusiveVoice runtime metered; LLM and carrier billed separately
Phone numbersIncluded, or bring your own Twilio or SIPBring your own Twilio or SIP account

See the full breakdown: Bland vs ElevenLabs.

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$40M+Revenue added in 5 months
250+Enterprises in production
<400msEnd-to-end latency
$0.11Per minute, all-inclusive
40+Languages supported

ElevenLabs alternative FAQ

No. Bland voices stand with the best in the industry. The real difference is the platform around the voice: Bland runs the full stack with no third-party LLM and is built for the most complex inbound calls.

Yes. ElevenLabs added an agents product in 2025, built on top of its voice models and running on a third-party LLM you bring. If agents are what you are buying, Bland is built for them end to end: one proprietary stack, no third-party model, tuned for complex inbound calls.

For complex, regulated inbound phone work, Bland: one proprietary stack with no third-party LLM for better latency, uptime, and data governance, voices on par with the best, and a platform built only for phone agents. ElevenLabs is a strong voice-model company whose agents product is newer and routes reasoning through a third-party LLM.

Ready to make the switch?

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