THE VERDICT
● GPT-Live-1 if conversation flow is the product — interruptions, overlap, turn-taking that feels human.
● ElevenLabs if how the voice sounds is the product. Still the quality benchmark.
● Gemini Flash Live if you are already in Google Cloud and procurement decides.
● Watch for: none of these published comparable per-minute pricing at launch.
They solve different halves
Voice has two hard parts. Making the audio sound like a person, and making the conversation behave like one. Most products are good at one and adequate at the other.
| GPT-Live-1 | ElevenLabs | Gemini Flash Live |
|---|
| Full-duplex | Yes | No | Speech-to-speech |
| Interruption handling | Native | You build it | Supported |
| Voice quality | Good | Benchmark | Good |
| Reasoning | Delegates to backend | You supply it | Gemini models |
| Pricing model | Not published at launch | Subscription | Per usage |
THE DELEGATION DESIGN IS THE REAL DIFFERENCE
Conversation needs to be fast. Reasoning needs to be good. One model doing both compromises on one of them, and voice products have historically compromised on the reasoning.
GPT-Live-1 splits them — a fast conversational layer that hands hard questions to a backend model. That is the right shape, and it is what to look for in anything that follows.
Which one
| If you are building... | Pick |
|---|
| A support line where callers interrupt | GPT-Live-1. That is the case it exists for |
| Narration, audiobooks, branded voice | ElevenLabs. Conversation is not the job |
| Inside an existing Google stack | Gemini Flash Live. Integration beats marginal quality |
| Budgeting before committing | Wait. Voice bills per minute and the numbers are not comparable yet |
FAQ
What does full-duplex actually change?
The model processes incoming speech while producing output, so interruptions are handled natively rather than as exceptions. That is how people talk and it is what turn-based systems get wrong.
Is ElevenLabs still worth it?
For voice quality, yes. It remains the benchmark on how the audio sounds, which is a different problem from how the conversation flows.
How do I compare pricing?
Voice is billed per minute rather than per token, and GPT-Live-1 pricing was not published at launch. Compare on minutes, not against text model rates.