Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
Itâs the first Human Interaction Model (HIM).
Readers added context they thought people might want to know
The 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-griâŚ
research.nvidia.com/labs/amri/projâŚ
tech-ish.com/2026/10/02/tavâŚ
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The fastest way to build a PAL is to start with one.
Starter Kits are ready-to-go PALs, AI you talk to face to face, for onboarding, candidate interviews, customer service coaching, compliance training and more. Customize one and go live in a few clicks.
maker.tavus.io
You built a PAL, so now put it where people can talk with it.
Deployments gives you three ways: a link anyone can open, a widget for your site, or an embed in your product. Pick one and hit Create, with no backend or API keys needed.
Deploy your PAL at maker.tavus.io
Tavus retweeted
At @tavus we spend a lot of time thinking about personality and behavior in AI, and how to bring the richness and nuance of human communication to models.
Excited to share our new paper on Contrastive Covariance Steering (CCS), a method for precisely controlling individual behaviors in LLMs without unintentionally changing other characteristics.
Training-free, closed-form LLM steering that removes confounds (topic, style) from the steering vector. Beats every steering baseline in 12/12 modelâdomain settings, +48â70% on AxBench.
arxiv.org/abs/2610.14025
Tavus retweeted
Replying to @hassaanraza
@hassaanraza (Co-Founder & CEO, @tavus) joined @tbpn to talk about Griffin, their new Human Interaction Model.
Last week, Griffin became the first model to pass the real-time video Turing test.
Now weâre hiring more people to build what comes next across research, engineering, safety and GTM, including forward deployed engineers and a marketing leader.
Join us: tavus.io/careers
Tavus retweeted
Just put two @tavus Griffin PALs into a conversation with each other... why does it feel like i'm thirdwheeling?
Glad you noticed the difference, Linus. Thanks for giving Griffin an early test!
Itâs important that Griffin meets us where we are. You should be able to take your time, and you shouldnât need to spell everything out.
Thanks for spending time with Griffin, Santiago, and letting everyone sit in on the conversation.
Getting it into the hands of early testers has been one of the best parts of this preview.
Few people have spent more time working on real-time video than Kwin, so this means a lot.
Thanks for testing Griffin early and sharing your experience and feedback!
We blew past the Turing test for voice agents about a year ago. I don't think we talk about this enough.
We have lots of data from real-world voice agent deployments. In contexts like customer support, people often forget they are talking to a voice agent. This is true even when the system tells people they are talking to an AI agent at the beginning of the session. (Which I think is a best practice that almost all AI agents should adhere to.)
So ... when will this happen for realtime, conversational AI video? Well, we're getting very close.
@tavus just released a new realtime video model that, at its best, passes the Turing test for conversational video. It's pretty amazing.
The model is full-duplex (it can talk and listen at the same time), and does vision and audio input and audio+video output in realtime. Both on the nascent conversational video benchmarks, and in my testing, it's a pretty big step forward.
Here's an unedited video of one of my conversations with the new model.
I think you can see a few interesting things here. When the model responds as quickly as you expect a human to respond, the experience is magical. The responses are conversational and natural; there's no leaning on stock filler phrases to hit the response time goals. The integration between the video and audio feels natural, which has historically been an uncanny valley thing that most video avatar experiences didn't quite get past. The model can do hand gestures! If you're deep into this stuff, you'll find that a little bit mind-blowing. And, in keeping with all the stuff that Tavus has released, the fact that the model can "see" as well as hear and talk is integral to the experience and a big part of what makes the conversation feel useful and interesting.
At the very beginning of the conversation, you can see that the model and I talk over each other. Which is something that happens a lot in human-to-human video call conversations. We both recover from this gracefully, which, again, has been something that rarely worked quite perfectly in previous generations of realtime video systems. Even more than the "when it works perfectly" capabilities, it's probably these recovery and robustness moments that get us all the way to experiences that feel completely natural.
A little more about why we built Griffin, in @hassaanraza's words.
Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isnât publicly available yet. Yesterdayâs announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
Weâre working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know theyâre interacting with AI, while providing an interface that removes the need to âspeak computerâ.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
Because itâs the first model that can be mistaken for a real person, Griffin requires safety considerations before it can be released publicly. The full research preview covers how it works, how we tested it and the safety measures that have to come first: tavus.io/griffin









