AiFlow vs Google Agent Platform
Google Cloud's enterprise agent stack, formerly Vertex AI, combining the Agent Development Kit, Agent Engine, and search.
Their Pricing Model
No flat fee. Metered on compute at about $0.0864 a vCPU hour, memory at about $0.0090 a GB hour, sessions at about $0.25 per thousand events, search at $1.50 to $6.00 per thousand queries, and model tokens on top.
Architectural Crux
Four meters running at once, and forecasting the bill means forecasting all four. There is no per-minute charge because there is no single number at all.
Where each architecture wins.
Where Google Agent Platform has the advantage
- Scale nobody else can match, and an SLA to go with it.
- Native integration with the rest of Google Cloud.
- The Agent Development Kit itself is excellent, which is why AiFlow builds on it.
- Procurement, compliance, and support that a large enterprise already has in place.
Where AiFlow has the advantage
- One number instead of four meters.
- Runs on a single machine you already own, with no cloud account required.
- Telephony, WhatsApp, and an embeddable widget are the product rather than an integration exercise.
- A working deployment is a compose file, not a platform migration.
Which one should you choose?
Choose Google Agent Platform when:
You are already deep in Google Cloud, you need that scale, and a platform team is available to build on it.
Choose AiFlow when:
You want a finished product rather than a platform, and a bill you can predict.
Simulate 3-Year Total Cost of Ownership.
Your scale.
Your numbers.
See how platform costs change as your conversations grow.
More room to grow. No platform meter running.
How we calculate this
Using the comparison rates stored in this project: Vapi at $0.05/minute. Excludes model, telephony, hosting, taxes, and operational costs. Vendor plans and inclusions differ; this is a platform-fee estimate, not a full operating-cost quote.