Google AntiGravity!!!!! Holy Shit the game has changed!!!!!

Just been talking to Gemini 3 about Antigravity and if it could replace my current stack and be more cost effective!!!!

Q: So, can you orchestrate? Will you be able to? Can it be an orchestration and logic layer like VAPI and Retell?

This is the million-dollar question.

The short answer is: Google Antigravity is not the layer itself (like Vapi); it is the factory where you build the layer. However, what you build inside it (using the new ADK and Gemini 3) creates a "Native Orchestration" that actually removes the need for Vapi or Retell entirely.

Here is the technical breakdown of how Antigravity + Gemini 3 disrupts the Vapi/Retell model:

1. The Architecture Shift: "Stitched" vs. "Native"

This is the most important distinction.

How Vapi / Retell work (The "Stitched" Stack):
How Antigravity works (The "Native" Stack):

2. Can it handle Logic & Interruption? (The ADK)

Vapi and Retell are famous for their "endpointing" (knowing when to stop talking if the user interrupts). Can Google do this?

Yes. This is where the Agent Development Kit (ADK) comes in.

The Logic Layer: Antigravity includes the ADK, a library that handles the state machine of the conversation.
Interruption: Because Gemini 3 supports "Bidirectional Streaming," it handles interruptions natively. If the user speaks while the AI is talking, the model's audio input stream detects it and halts the audio output stream immediately—logic you historically paid Vapi to handle for you.

3. The Trade-Off: "Buy" vs. "Build"

FeatureVapi / RetellGoogle Antigravity + Vertex AIOrchestrationPre-packaged. You get a dashboard where you toggle "Interruption Sensitivity."Code-First. You write the logic in Python/Node using the ADK (e.g., agent.on_interrupt(stop_speaking)).TelephonyBuilt-in. They give you a phone number and handle the SIP trunking (via Twilio/Vonage).Bring Your Own. You likely need to connect your own telephony provider (Twilio) to the Google agent, though Google Cloud CCAI handles this for enterprise.CostPer-minute markup. You pay Vapi + LLM + Transcriber + Synthesizer.Token-based. You pay for Gemini 3 tokens (Audio In/Out). Generally cheaper at scale.LatencyLow, but limited by network hops.Ultra-Low. Single model inference.

Summary: Will it replace them?

If you are a Developer: Yes. Antigravity gives you the power to build a "Vapi-class" orchestrator yourself, but with lower latency and lower cost because you are cutting out the middleware markup and the STT/TTS hops.
If you are a Business User: No. Vapi and Retell are still easier to "plug and play" if you just want a phone number that works in 5 minutes. Antigravity is a developer tool.

What Antigravity can do better than Vapi:

Because Antigravity agents have browser control (which Vapi lacks), your voice agent can do things Vapi can't.

Vapi Agent: "I can book that appointment." (Triggers an API call).
Antigravity Agent: "I can book that." (Actually opens the calendar web page in a headless browser, clicks the slot, and verifies the confirmation screen visibly).

You are currently paying a "tax" on every layer of your stack (Vapi for orchestration, 11Labs for voice, Deepgram for listening, OpenAI for thinking). Google's "Antigravity" (Gemini 2.0 Live API) collapses all four of those layers into a single model call.

Here is the breakdown of the math.

1. The Cost Comparison (Per Minute)

Your Current "Stitched" Stack (Estimated)

Orchestration (Vapi): $0.05 / min (Platform fee)
Ears (Deepgram/Nova): ~$0.01 / min
Brain (GPT-4o): ~$0.05 / min (varies by token usage)
Mouth (11Labs): ~$0.10 - $0.18 / min (depending on tier/model)
TOTAL: ~$0.21 - $0.30 per minute

The Google "Native" Stack (Gemini 2.0 Flash Live) Google charges by "Tokens," which sounds confusing/expensive, but when you convert it to time, it is incredibly cheap.

Input Audio (Listening): ~$3.00 per 1 million tokens.
Output Audio (Speaking): ~$12.00 per 1 million tokens.
TOTAL: ~$0.04 - $0.05 per minute

Result: Google is roughly 80% cheaper than the Vapi/11Labs stack.

2. Why is it so much cheaper?

You are cutting out the "middlemen."

No Vapi Markup: Vapi charges $0.05/min just to exist in the call. Google charges $0 for the connection; you only pay for the data flowing through it.
No "Translation" Costs: In your current stack, you pay to turn Audio -> Text (Deepgram), then Text -> Text (LLM), then Text -> Audio (11Labs). In Gemini 2.0, it is just Audio -> Audio. You skip the conversion steps entirely.

3. The "Hidden" Costs (Watch Out For This)

While the voice is cheaper, here is where Google could surprise you if you aren't careful:

The "Silence" Fee: In the Google Live API, you pay for the open microphone even when the user isn't speaking (because the model is "listening" to the silence to detect interruptions).
Context Caching: If you load a massive 500-page "Maintenance Protocol PDF" into the agent's memory for every single call, you pay to process that text every time.

4. Summary for Your Business Model

Since you are charging per unit ($1.25/unit) and want to keep margins high (64-70%), switching to Google is the single best thing you can do for your unit economics.

At 100 clients (200k units):
Vapi Stack Cost: High variable cost eats into your $1.25 margin.
Google Stack Cost: Low variable cost significantly increases your net profit per unit.

The reality is that Google’s "Native Stack" (Gemini 2.0 Flash) is not only cheaper than your current Vapi + 11Labs stack, but Context Caching specifically makes it dirt cheap to handle complex property management tasks.

Here is the breakdown of why it costs less, not more.

1. The "Context Caching" Savings Mechanism

In your current model (Vapi), if you want the AI to know your "Emergency Maintenance Protocols" (a 50-page PDF), you have to pay to feed that text into the model every single time a tenant calls.

Without Caching (The "Vapi/Standard" Way):

Scenario: Tenant calls. You send the 50-page manual (25k tokens) so the AI knows what to do.
Cost: You pay for 25k tokens of processing.
Next Call: 5 minutes later, another tenant calls. You pay for those same 25k tokens again.
Result: You are paying to "re-read the book" every time the phone rings.

With Google Context Caching:

Scenario: You upload the 50-page manual once in the morning. Google "caches" (saves) it in the model's short-term memory.
Cost: You pay a tiny "storage fee" (approx. $1.00 per 1 million tokens per hour).
The Calls: When 100 tenants call that day, you pay near-zero for the manual tokens because the model already knows them. You only pay for the new audio (the tenant speaking).
Savings: This reduces the input cost by ~90% for heavy operational documents.

2. The Direct Price Comparison

FeatureYour Current Stack (Vapi/11Labs/GPT-4)Google Antigravity (Gemini 2.0 Flash)Orchestration Fee$0.05 / min (Vapi platform fee)$0 (No platform fee)Listening (STT)$0.01 / min (Deepgram)~$0.006 / min (Gemini Audio In)Thinking (LLM)$0.03+ / min (GPT-4o)Included in Audio In/Out tokensSpeaking (TTS)$0.15 / min (11Labs)~$0.03 / min (Gemini Audio Out)TOTAL~$0.24 per minute~$0.04 - $0.06 per minute

Verdict: Google is roughly 4x–6x cheaper per minute of conversation.

3. The "Hidden" Strategic Advantage: Latency

Cost isn't even the best part. Latency is.

Vapi Stack: Audio → Text (200ms) → LLM (500ms) → Text (100ms) → Audio (400ms) = ~1.2s delay.
Google Stack: Audio → Audio (Native) = ~300–500ms delay.
For a "Leasing Agent" trying to sound natural, that 700ms difference is the gap between "robotic" and "human."

Your Welcome!!!!!!!

0 comments