On June 9th, Google attached a billing rate to something that used to require a trained professional wearing a headset in a glass booth: live interpretation. The model is called Gemini 3.5 Live Translate, and in the next five minutes you’ll know what actually shipped, what it costs, which claims are proven, and whether you should use it, build on it, or hold off.
The verdict up front: this is a real release, it landed on three surfaces at once, and the pricing is aggressive. You can test it for free today. But nearly every performance claim in circulation traces back to Google itself, early hands-on reports describe real accuracy and turn-taking gaps, and it’s a preview model with no service guarantees. So, use it now, and trust it slowly.
Everything below comes from Google’s pricing tables, the official model documentation, the DeepMind model card, and the launch coverage, cross-checked against each other. The receipts are linked at the bottom.
What actually shipped
Gemini 3.5 Live Translate is a streaming speech-to-speech model. You talk, and a few seconds later it speaks your words in another language. Google says it auto-detects more than 70 languages and preserves the speaker’s intonation, pacing, and pitch. It rolled out in three places at once.
For everyone, it’s now the engine inside the Google Translate app on Android and iOS, globally and free. One naming detail worth getting straight, because it confuses people: the “Live translate” feature itself is not new. It first appeared in the app in August 2025. A headphone-based beta followed in December 2025. What changed in June is the model underneath, and Android also picked up a listening mode that plays the translation quietly through your earpiece.
For developers, it’s available in public preview through the Gemini Live API and Google AI Studio under the model ID gemini-3.5-live-translate-preview.
For enterprises, it’s headed into Google Meet, currently in private preview for select Workspace customers, with a broader rollout promised later this year.
Why this one is different
Most translation tools you’ve used run a relay race. Your speech becomes text, the text gets translated, and a synthetic voice reads the result back. That handoff chain is why old translation apps gave us the international tourist ritual where you type a sentence, rotate your phone 180 degrees, and present it to a stranger like a tiny glowing peace treaty.
This model skips the relay. It’s audio in, audio out, and it generates translated speech continuously while you’re still talking, staying a few seconds behind you instead of waiting for you to finish. Google’s pitch is that the output keeps your voice’s character rather than flattening you into robot narrator. That pitch, to be clear, is Google’s own description of Google’s product.
The spec sheet
The official model page is refreshingly blunt about what this thing is and is not. Input is audio only. Output is translated audio plus a text transcript. The context window runs 131,072 tokens in and 65,536 out. Per the DeepMind model card, it’s built on Gemini 3 Pro.
Now the off switches, and there are a lot of them: no function calling, no structured outputs, no thinking, no caching, no batch API, no code execution, no search grounding. This is a translation pipe, full stop, and any app logic you want (routing calls, saving transcripts, updating your CRM) has to live in your own backend, triggered by the transcripts it hands you.
The pricing math
This is where it gets interesting. During the public preview, the free tier costs nothing for both input and output. Google is letting you prototype the entire flow for zero dollars.
On the paid tier, audio bills at 25 tokens per second. Input runs $3.50 per million tokens, which Google’s own footnote converts to $0.0053 per minute. Output runs $21.00 per million tokens, or $0.0315 per minute. Combined, Google’s published effective rate is about $0.0368 per minute of audio. Run a conversation for a full hour and you’ve spent roughly $2.21.
Both directions bill, so a two-way conversation counts the speech going in and the translation coming out. Even so, the number is small enough that “can we afford live translation” stops being the question. The question becomes whether the output is good enough.
The Meet jump
Speech translation in Google Meet used to cover five languages. The new model pushes that past 70, and Google says it unlocks more than 2,000 language combinations in a single meeting. It also drops the old limitation of routing everything through English.
Before your ops team gets excited, note what’s missing: this is a private preview for selected Workspace customers, and Google has published no pricing, no tier requirements, and no general availability date for it. Grab is testing the model for driver and traveler calls, a channel Google says handles over 10 million voice calls per month, but that figure comes from Google’s launch post.
The receipts nobody reads
Here’s the part that separates this from a press release. Google’s model card evaluates the system on translation quality (using an automated metric called AutoMQM), latency, and speech naturalness. Those are Google’s own internal evaluations. The glowing launch quotes from partners like Agora, LiveKit, and Vision Agents appear in Google’s own announcement, which means they’re testimonials Google selected.
Independent testing is still thin six weeks in, and what exists is mixed. Early hands-on coverage flags accuracy problems and awkward turn-taking in real conversations. There’s also a structural issue reviewers keep raising: some languages save the verb for the very end of the sentence, which means a streaming translator is essentially guessing the punchline before the joke is over. German speakers, you know exactly what I mean.
Add the standard preview caveats. There’s no SLA, the model can change before general availability, and preview pricing can change too. And with 2,000+ language pairs, quality will not be uniform. Your pair might be great. It might not.
So what
Do this: update the Google Translate app and try Live Translate with headphones, because it costs you nothing and the demo value alone is worth it. If you build things, prototype on the free preview tier this month while input and output are free.
Skip this: putting it in front of customers without a fallback path and without testing your exact language pairs under real conditions, with accents, background noise, and people talking over each other.
Wait on this: any enterprise planning built around Meet. Private preview, select customers, zero published pricing. There’s nothing to plan against yet.
The takeaway you can steal: Google just made live translation cheap and effortless to try but proving it works for your languages is still your job.