Major takeaways
Who should pick Bland AI over Vapi? Operations teams and contact-centre leaders who want a no-code builder, bundled phone numbers, and managed telephony without writing code.
Who should pick Vapi over Bland AI? Developers and technical founders building custom voice products who need full control over LLM choice, telephony stack, and voice-provider selection.
How do their pricing models differ? Bland AI charges per minute with bundled telephony; Vapi charges per minute but bills LLM, speech-to-text, text-to-speech, and telephony separately based on usage.
If you care about X, pick Y
| If you care about | Pick | Why |
|---|---|---|
| Building without code | Bland AI | Visual builder with templates; no API integration required |
| Full control over LLM and voice providers | Vapi | Bring-your-own OpenAI, Anthropic, ElevenLabs, Deepgram, or other providers |
| Bundled telephony and phone numbers | Bland AI | Phone numbers and carrier in per-minute rate |
| Transparent itemised billing | Vapi | Separate line items for compute, telephony, and speech services |
| Enterprise compliance documentation | Bland AI | Published SOC 2 Type II and HIPAA compliance statements |
| Developer-first API experience | Vapi | SDK-first design with WebSocket control and function-calling primitives |
How we evaluated
We reviewed vendor documentation, pricing pages, and published feature lists for Bland AI and Vapi as of October 2026. Review coverage from G2, Capterra, and TrustRadius was consulted where available. Pricing figures reflect list rates published on vendor sites; actual per-minute costs depend on usage, contract terms, and third-party provider rates. We did not build test agents, place calls, or measure latency. Compliance statements reflect vendor-published certifications; readers should request documentation directly for regulatory requirements. Last updated: October 2026.
What each platform does
Bland AI is an enterprise phone agent platform built for operations teams and contact centres automating inbound and outbound calls. Users build agents in a visual workflow builder or via API, deploy phone numbers from Bland AI's bundled telephony, and manage campaigns from a web dashboard. The platform handles appointment booking, lead qualification, customer-support deflection, and outbound reminders. Bland AI states it processes millions of calls per month across enterprise customers, according to vendor documentation. Pricing is per minute with telephony included.
Vapi is an API-first developer platform for building custom voice AI products. Developers integrate Vapi via SDK, control calls over WebSocket, and bring their own LLM (OpenAI, Anthropic, Groq), speech-to-text (Deepgram, AssemblyAI), text-to-speech (ElevenLabs, PlayHT, Cartesia), and telephony (Twilio, Vonage, Telnyx). Vapi provides the orchestration layer, interruption handling, and function-calling primitives. Startups and technical teams use it to build voice products, AI receptionists, and custom call workflows. Pricing is per minute for orchestration; LLM, speech, and telephony costs are billed separately by the respective providers.
Feature comparison
| Capability | Bland AI | Vapi |
|---|---|---|
| Build model | No-code visual builder + API | API-first SDK, WebSocket control |
| Inbound calls | ✓ Bundled phone numbers | ✓ Bring-your-own telephony or Vapi numbers |
| Outbound calls / campaigns | ✓ Campaign dashboard, batch dialing | ✓ API-driven outbound, no campaign UI |
| Telephony | Bundled carrier and numbers | Bring-your-own Twilio/Vonage/Telnyx or Vapi SIP |
| LLM choice | Vendor-hosted models | Bring-your-own OpenAI, Anthropic, Groq, others |
| Voice / TTS provider choice | Limited; vendor-selected voices | Bring-your-own ElevenLabs, PlayHT, Cartesia, Deepgram |
| Languages | 30+ languages (as published) | Depends on chosen TTS/STT provider |
| Interruption handling | ✓ Configurable turn-taking | ✓ Low-latency interruption, tunable sensitivity |
| Warm transfer / human handoff | ✓ Transfer to phone number | ✓ Transfer via SIP or PSTN |
| Function calling / tool use | ✓ API actions, CRM lookups, booking | ✓ Custom functions via WebSocket |
| CRM and calendar integrations | Native HubSpot, Salesforce connectors | API-based; developer implements |
| Call recording, transcripts, analytics | ✓ Dashboard with call logs and transcripts | ✓ Logs via API; analytics developer-built |
| Compliance statements | SOC 2 Type II, HIPAA (as published) | SOC 2 Type II (as published); HIPAA on request |
| Concurrency limits | Enterprise tier: custom limits | Not publicly documented; scales per account |
Pricing and cost per minute
Bland AI pricing
Bland AI charges per minute with telephony bundled. Published tiers as of October 2026, based on vendor documentation:
| Tier | Per-minute rate | Includes | Minimum |
|---|---|---|---|
| Starter | $0.09/min (reported) | LLM, TTS, STT, telephony, phone numbers | Not specified |
| Growth | Custom quote | LLM, TTS, STT, telephony, phone numbers, priority support | Annual contract |
| Enterprise | Custom quote | All Growth features, dedicated infrastructure, SLA | Annual contract |
Source: Bland AI pricing page, October 2026
Bland AI's per-minute rate reportedly includes compute, speech services, and carrier costs. Contract minimums and volume discounts are not publicly listed. Overages and international calling rates are not specified on the pricing page. Teams should request a quote to confirm all-in costs at expected volume.
Vapi pricing
Vapi charges per minute for orchestration; LLM, speech-to-text, text-to-speech, and telephony are billed separately by the respective providers. Published tiers as of October 2026:
| Tier | Orchestration rate | What it includes | LLM / TTS / STT / Telephony |
|---|---|---|---|
| Developer | $0.05/min | Vapi orchestration, function calling, WebSocket API | Billed separately by OpenAI, Deepgram, ElevenLabs, Twilio, etc. |
| Production | Custom quote | Orchestration, dedicated support, SLA | Billed separately |
Source: Vapi pricing page, October 2026
A typical call using OpenAI GPT-4, Deepgram STT, ElevenLabs TTS, and Twilio telephony might cost $0.05 (Vapi) + $0.02–0.06 (LLM tokens) + $0.01–0.02 (STT) + $0.02–0.05 (TTS) + $0.01–0.02 (Twilio per-minute) = approximately $0.11–0.20 per minute. These are illustrative estimates based on published provider pricing; actual costs depend on conversation length, model choice, and voice provider. Vapi's itemised model means teams pay only for what they use, but also carry the complexity of managing multiple vendor accounts.
What a month of calls might cost
To estimate monthly spend:
- Average call length (minutes per call). Measure from logs or assume 3–5 minutes for qualification, 1–2 minutes for appointment confirmation.
- Call volume (calls per month).
- All-in per-minute rate. For Bland AI, the published per-minute rate; for Vapi, orchestration + LLM + STT + TTS + telephony per minute.
- Platform fees. Vapi Developer tier has no monthly platform fee; Bland AI tiers may include minimums (not publicly listed).
Formula: (average call length × call volume × all-in per-minute rate) + platform fees + overages.
Illustrative example (not a benchmark): A team running 1,000 calls per month at an average 4-minute call length would consume 4,000 minutes. At Bland AI's $0.09/min, that is $360/month. At Vapi's estimated $0.15/min all-in (orchestration + providers), that is $600/month. These are illustrative assumptions; actual spend depends on contract terms, provider selection, and usage patterns. Teams should model their own call profiles and request quotes from both vendors.
What users say
Public review volume for Bland AI is limited; the recurring themes below are drawn from the available G2 / Trustpilot / TrustRadius coverage.
Bland AI user feedback
Reviewers on G2 and Capterra note Bland AI's ease of deployment for non-technical teams. The visual builder and bundled telephony are cited as strengths for operations teams without engineering resources. Some users report that the platform's vendor-hosted LLM and voice options limit customization compared to bring-your-own-model platforms. Pricing transparency is flagged as a concern; multiple reviewers note that Growth and Enterprise tiers require custom quotes, which can extend procurement cycles.
Vapi user feedback
Vapi's developer community on GitHub and Discord highlights the platform's flexibility and low-latency interruption handling. Users building custom voice products appreciate the bring-your-own-provider model and WebSocket control. Some developers report that the itemised billing model adds complexity; tracking costs across Vapi, OpenAI, Deepgram, ElevenLabs, and Twilio requires careful monitoring. A few users note that the lack of a visual builder or campaign dashboard means non-technical teams cannot deploy Vapi without engineering support.
Strengths and gaps
What Bland AI does well
No-code deployment. Visual builder and templates let operations teams launch agents without writing code. Bundled telephony means no carrier integration work.
Managed infrastructure. Bland AI handles LLM hosting, speech services, and telephony in one per-minute rate. Teams avoid managing multiple vendor accounts.
Enterprise compliance. Published SOC 2 Type II and HIPAA compliance statements, according to vendor documentation, support regulated industries.
Campaign management. Dashboard for batch outbound dialing and call analytics is built in, which fits contact-centre workflows.
Where Bland AI has gaps
Limited model choice. Vendor-hosted LLM and voice options reportedly restrict customization. Teams cannot bring their own OpenAI or Anthropic models.
Pricing opacity. Growth and Enterprise tiers require custom quotes. Per-minute rates at volume and international calling costs are not publicly listed.
Telephony lock-in. Bundled carrier means teams cannot bring existing Twilio or Vonage numbers without migration, based on vendor documentation.
What Vapi does well
Full provider control. Bring-your-own LLM, TTS, STT, and telephony. Teams can optimize for cost, latency, or voice quality by swapping providers.
Developer-first API. SDK and WebSocket control fit technical teams building custom voice products. Function-calling primitives support complex workflows.
Transparent itemised billing. Separate line items for orchestration, compute, and telephony. Teams pay only for what they use.
Low-latency interruption. Vapi's interruption handling is cited by developers as responsive and tunable, according to community feedback.
Where Vapi has gaps
No visual builder. Non-technical teams cannot deploy Vapi without engineering resources. No campaign dashboard or call-management UI.
Billing complexity. Managing accounts with Vapi, OpenAI, Deepgram, ElevenLabs, and Twilio adds operational overhead. Cost tracking requires custom tooling.
Limited compliance documentation. SOC 2 Type II is published; HIPAA compliance is available on request, according to vendor documentation. Teams in regulated industries should confirm certifications before deployment.
Which use cases fit each
| Use case | Stronger fit | Why |
|---|---|---|
| Inbound lead qualification and speed-to-lead | Bland AI | Bundled telephony and visual builder deploy faster for operations teams |
| Appointment booking and reminders | Bland AI | Campaign dashboard and native CRM integrations fit booking workflows |
| After-hours reception and routing | Either | Both handle inbound calls and warm transfer; choice depends on build preference |
| Outbound sales calling at scale | Bland AI | Batch dialing and call-management dashboard built in |
| Customer-support deflection | Bland AI | No-code builder and managed infrastructure suit support teams |
| High-volume contact-centre overflow | Bland AI | Enterprise tier with dedicated infrastructure and SLA |
| Developer building a custom voice product | Vapi | Full control over LLM, TTS, STT, and telephony stack |
| Startups optimizing per-minute costs | Vapi | Itemised billing lets teams swap providers to reduce costs |
Pick Bland AI if you...
You need a no-code builder and want to deploy agents without engineering resources.
You prefer bundled telephony and a single per-minute rate that includes LLM, TTS, STT, and carrier costs.
You run outbound campaigns and need a dashboard for batch dialing and call analytics.
You operate in a regulated industry and require published SOC 2 and HIPAA compliance statements.
Pick Vapi if you...
You are a developer or technical team building a custom voice product with specific LLM and voice-provider requirements.
You want full control over your telephony stack and the ability to bring existing Twilio or Vonage numbers.
You prefer itemised billing and want to optimize per-minute costs by swapping providers.
You need low-latency interruption handling and WebSocket control for complex call workflows.
Note: if the calls you're automating are inbound sales conversations that need to sit alongside an outbound AI SDR in one platform, teams in that position typically also evaluate 11x's Julian.
Verdict
Bland AI is the stronger fit for operations teams, contact centres, and revenue leaders who want to automate calls without writing code. The visual builder, bundled telephony, and campaign dashboard deploy faster than API-first platforms. Teams running outbound appointment reminders, inbound qualification, or support deflection will find Bland AI's managed infrastructure and native CRM integrations reduce time to production. The trade-off is limited model choice and pricing opacity; Growth and Enterprise tiers require custom quotes, and teams cannot bring their own LLM or telephony provider.
Vapi is the better starting point for developers and technical founders building custom voice products. Full control over LLM, TTS, STT, and telephony means teams can optimize for cost, latency, or voice quality by swapping providers. The itemised billing model is transparent but adds complexity; teams must manage accounts with Vapi, OpenAI, Deepgram, ElevenLabs, and Twilio. Vapi fits startups building AI receptionists, voice-enabled SaaS features, or custom call workflows where the engineering team owns the build.
Practical next steps: build the same short test flow on both platforms (a 2-minute inbound qualification call or a 1-minute appointment reminder). Measure setup time, call quality, and all-in per-minute cost at your expected volume. Request compliance documentation from both vendors if you operate in a regulated industry. Confirm contract minimums and cancellation terms before committing to an annual deal.
Frequently asked questions
Is Bland AI cheaper than Vapi?
Bland AI's published per-minute rate is $0.09 on the Starter tier, which reportedly includes LLM, TTS, STT, and telephony. Vapi's orchestration is $0.05/min, but LLM, speech, and telephony are billed separately; an all-in rate might be $0.11–0.20/min depending on provider choice. At low volumes, Bland AI may be cheaper. At high volumes, Vapi's itemised model lets teams optimize costs by swapping providers. Request quotes from both vendors at your expected call volume.
Which is easier to build with if I can't code?
Bland AI. The visual builder and templates let non-technical teams deploy agents without writing code. Vapi is API-first and requires engineering resources to integrate the SDK, configure providers, and build call workflows. If your team does not have a developer, Bland AI is the only option between these two platforms.
Can I bring my own phone numbers or carrier to each?
Vapi supports bring-your-own Twilio, Vonage, or Telnyx numbers, according to vendor documentation. Bland AI bundles telephony and phone numbers in the per-minute rate; bringing existing numbers reportedly requires migration or may not be supported on lower tiers. Teams with existing carrier contracts should confirm number portability with Bland AI before committing.
Which handles outbound calling campaigns better?
Bland AI. The platform includes a campaign dashboard for batch dialing, call scheduling, and analytics. Vapi is API-driven; outbound calls are triggered programmatically, and there is no campaign-management UI. Teams running high-volume outbound reminders, confirmations, or sales calls will find Bland AI's dashboard faster to deploy.
Are Bland AI and Vapi HIPAA compliant?
Bland AI publishes SOC 2 Type II and HIPAA compliance statements on its website, according to vendor documentation. Vapi publishes SOC 2 Type II; HIPAA compliance is available on request. Teams in healthcare or other regulated industries should request a Business Associate Agreement (BAA) and compliance documentation directly from each vendor before deploying. Compliance depends on how the platform is configured and deployed; neither vendor's certification alone makes your use case compliant with HIPAA or TCPA.
Can either transfer a call to a human?
Yes. Both platforms support warm transfer. Bland AI transfers to a phone number via its bundled telephony. Vapi transfers via SIP or PSTN, depending on the telephony provider you bring. Both platforms can hand off context (caller intent, transcript) to the human agent, according to vendor documentation.
What do users complain about most?
For Bland AI, reviewers on G2 and Capterra cite pricing opacity (Growth and Enterprise tiers require custom quotes) and limited model choice (vendor-hosted LLM and voice options). For Vapi, developers on GitHub and Discord note billing complexity (managing multiple provider accounts) and the lack of a visual builder or campaign dashboard for non-technical teams. Both platforms have thin public review coverage; teams should request references from vendors.
How does 11x's Julian compare to Bland AI and Vapi?
Julian is 11x's AI phone agent for inbound speed-to-lead and qualification, sold as part of the 11x platform alongside Alice (outbound AI SDR). Julian is a packaged sales agent rather than a general-purpose voice-building platform. Teams building custom voice products or automating non-sales calls (support, booking, reception) typically compare Bland AI and Vapi more directly. Julian fits revenue teams that want inbound voice and outbound email in one system.
Which platform has better latency?
Vapi's developer community cites low-latency interruption handling as a strength, according to GitHub and Discord feedback. Bland AI does not publish latency benchmarks. Actual latency depends on LLM choice, TTS provider, network conditions, and call volume. Teams should test both platforms with their expected call profile to measure response time.
Can I use either platform outside the US?
Both platforms support international calling, but costs and availability vary. Bland AI's bundled telephony reportedly covers select international markets; teams should confirm coverage and per-minute rates for their target countries. Vapi's international support depends on the telephony provider you bring (Twilio, Vonage, Telnyx). Both platforms' LLM and TTS providers support multiple languages; confirm language coverage for your use case before deploying.
Last updated: October 2026.
