NVIDIA just released an open source AI model for self driving
cars. At CES 2026, Jensen Wang
unveiled Alpa Mayo, a 10 billion parameter reasoning model that
can explain why it makes every driving decision and the first
production vehicle to use it will be the 2025 Mercedes-Benz
CLA, launching in the United States in the first quarter of
2026. It's a real You can buy it in a
few months with Nvidia's full self driving stack built in.
Jensen Wong called this the ChatGPT moment for physical AI,
the point where machines begin to understand, reason and act in
the real world. And the question is whether
NVIDIA just leapfrog Tesla in the race to autonomous driving
by giving every other automaker access to technology that Tesla
has spent a decade developing in secret.
Now, the technical specs are pretty good.
Nvidia's platform runs on two Drive 4 chips delivering over
2000 teraflops of compute power, roughly 1000 trillion operations
per second. Tesla's Hardware 4 is believed
to be in the few 100 tops range and mobilize upcoming a key
ultra is rated at 176 tops. Nvidia's offering five to six
times more processing power than anyone else on the market.
They up IO model weights are available on hugging right now.
You can check them out yourself and the simulation framework is
on GitHub. NVIDIA released 1700 hours of
real driving data for anyone to use.
And in this episode we're going to be talking about what the
demo looked like, who's partnering with NVIDIA and why
this open source approach could change everything.
And we're right into that Right after this very short break,
NVIDIA demonstrated the system live in San Francisco.
The transportation editor from The Verge got a ride in a
Mercedes-Benz CLA equipped with Nvidia's Level 2 Plus system. 40
minutes to the city traffic and the route included delivery
trucks, cyclists, pedestrians, four way stops, traffic lights,
double parked cars and unprotected left turns.
The car handled all of it without disengagements and
according to this, there were no crashes and no hiccups during
the entire ride. They said that NVIDIA showed
would go toe to toe with Tesla's Full Self driving under the most
complex circumstances. That's a significant claim right
now. Now, the demo showed specific
behaviors that suggests the AI is reasoning rather than just
pattern matching. At one point, the vehicle
approached an intersection blocked by a truck.
The NVIDIA system for a slow to let pedestrians cross then
executed a wide maneuver around the obstacle.
That kind of nuanced decision making, combining caution and
assertiveness the way a human driver would, is what the Epamio
model is designed to produce. The AI uses chain of thought
reasoning, which means it generates a step by step
explanation of its logic before executing each action.
That internal monologue is not just for debugging them.
It's designed to help the system handle rare edge cases by
explicitly reasoning about cause and effect.
Tesla's FSD does not do this. Tesla's neural networks are
black boxes that produce outputs without explanations.
The search strategy is also different from Tesla's.
Nvidia's platform supports cameras, radar, lidar and
ultrasonics, and a full 360° array.
Tesla famously removed radar from his vehicles in 2021, has
never used lidar, relying entirely on cameras for full
self driving. Nvidia's arguing that redundancy
is necessary for safety, and the demo vehicle used a combination
of cameras and radar to perceive its surroundings.
Now this approach is safer and more robust than camera only
systems, especially in poor visibility or when objects are
occluded. NVIDIA has partnered with sensor
suppliers like Eva, High C and Sony and RB to create a
validated ecosystem of hardware that works with its software
stack, and automakers can mix and match components without
worrying about compatibility. There's no walled garden for
this thing. Now.
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Now. The partnership list is very
impressive. Mercedes-Benz is first launching
the CLA with what they are calling MB Drive Assist Pro
capable of point to point city navigation under driver
supervision, and Huang said the CLA is safest car in the world,
sending its Euro NCAP 5 star rating.
Jaguar Land Rover has a multi year deal to use Nvidia's
platform for level 4 autonomy and future vehicles.
Lucid is in granting the full stack into upcoming models.
Uber is back in the autonomous vehicle game, working with
NVIDIA to potentially deploy robo taxis or automated delivery
vehicles. The Tier 1 suppliers are on
board too. Bosch, ZF, Magna, and Quanta are
all building electronic controls and units around Nvidia's
architecture. That means car companies can buy
pre integrated hardware from their existing suppliers and
just drop in Nvidia's system without building everything from
scratch. I'm an open source advocate.
I love that Nvidia's doing this and the open source approach is
what makes this different from everything else in the market.
Tesla's full self driving software is entirely
proprietary. You can't buy it, you can't
license it. They're by giving it away.
You can't study it, we don't know how it works.
Mobilized technology is also proprietary.
Waymo and Cruz develop full self driving stacks, but they use
them exclusively for their own robotaxi fleets.
NVIDIA is the first company to release a production grade
autonomous driving. EI is open source.
This is a clear bid to become the kind of like Android of
autonomy while Tesla continues to keep its FSD stack completely
closed, similar to Apple. And the implication is that any
automaker without Tesla's decade of in house AI development can
now get equivalent technology right off the shelf.
It's free, you get it, all you have to do is buy the parts and
build this software around it and you're good to go.
Now if Mercedes actually ships a car in Q12026 that has similar
capabilities to Tesla's FSD, it is based on an open source
system any automaker can buy. It could commoditize level 2
plus autonomous systems. Advanced driver assistance would
no longer be the secret sauce of a few companies, would be a
feature any car maker can implement with Nvidia's help.
That puts pressure on Tesla, which has never faced an equal
capable rival system in production vehicles.
It also challenges Mobileye, whose business model depends on
being the dominant ADAS supplier.
Qualcomm announced new AI features for cars at CES, but
Snapdragon Ride platform is still significantly behind
NVIDIA in raw performance and NVIDIA laid out it that
compresses the timeline to widespread autonomy.
By mid 2026, they expect Level 2 plus urban and Hwy. driving with
automated lane changes, traffic light recognition, and point to
point navigation. By the end of 2026, they plan to
cover the entirety of the United States in terms of operational
design domain and add autonomous parking.
Late 2026 will bring a small scale Level 4 trial similar to
Waymo's early ROBO taxi pilots and by 2027 NVIDIA expects
partner robotaxi deployments to begin.
By 2028, they're targeting personally owned Level 4
vehicles and Level 3 hands off driveway and Hwy. driving into
production cars. That is an aggressive schedule.
It depends on regulatory approvals and the confidence of
automaker partners though. But the message is very clear.
NVIDIA is committing to rapid iteration and deployment of this
open source software. Now, the business model is
significant. Nvidia's automotive division
currently generates about $600 million in revenue, compared to
51 billion in their core AI and cloud business.
Now, if this works, every vehicle that uses Nvidia's
platform brings recurring revenue for chips, software
licenses and cloud services. NVIDIA also introduced the Rubin
Platform, a new data center system for training autonomous
driving model. That means they capture value
both in the vehicle, in the cloud.
As fleets scale up, Jensen Wong said the goal is that someday
every car in every truck will be autonomous.
NVIDIA is working toward that future with the foundation laid
out at CES 2026. They have made a strong case
that will make the key architectures of that future.
I think it's probably the best announcement at CES 2026 as far
as a regular person goes, as far as automakers go, because
everybody uses a car, right? And if you have ever used Uber,
you know how important it is to get your car there on time and
also get you to where you're going.
But also, it's not the perfect system.
Once people are taken out of that equation and we can have
robotaxis and we'll have to work with those robotaxis or work as
those robotaxis, it's not just going to be Tesla anymore.
People will be able to compete and NVIDIA is helping them.
So this is a strategic frame too.
Listen to this. Jensen said that Chet TBT is
similar to this, and he believes this is the moment that
reasoning AI will do for robots and vehicles what large language
models did for text. For us, the ability to explain
decisions is not just about debugging anymore.
Governments want this. They want to understand why an
autonomous vehicle made a particular choice before they
approve it for public roads. And by exposing that reasoning
trace, NVIDIA is addressing concerns about black box AI in
safety. Critical application regulators
and researchers can inspect how the system drives at each
decision, and that transparency can make NVIDIA powered vehicles
easier to validate and certify than systems that cannot explain
themselves. Now, the challenges are
absolutely real here. There's a lot of work to do.
Automakers traditionally want to control their own stack.
Handing over the core driving AI to NVIDIA means giving up a lot
of that control. But the presence of Mercedes,
JLR and Lucid on board suggest a shift towards collaboration.
If the big players can do it, if they jump on board, I mean
Mercedes come out now. Public acceptance will require
flawless safety records though. NVIDIA focus on safety,
including their Halos framework for validation and functional
safety is aiming at building trust with government.
The competitive response will also shape outcomes here.
And also they're building trust with the public.
They want you and me to feel comfortable in a car with NVIDIA
stacks. Kind of Tesla opens parts of its
stack. Or a mobile eye undercuts NVIDIA
on cost. The market could go wild here.
NVIDIA also released ELPA SIM, which is an open source
simulation framework for testing autonomous vehicles in virtual
environments. And this is cool because
engineers can create realistic scenarios with configurable
traffic, whether in sensor modes that run the AI through edge
cases, without putting anyone at risk.
They don't need an actual car to do this.
It's going to be training the AI on the infinite amounts of
situations that we could hit on the road.
Then they're going to run the AI through edge cases without
putting any people in a vehicle. The 1700 hours of driving data
released alongside it covers diverse graphical locations and
conditions, including rare and complex situations that are hard
to capture a normal testing. Like just bad drivers.
You see them every day. You see a bad driver or you'll
see somebody who, this is a green light and they're on their
cell phone for a while. You have to hog at them.
Those kind of things happen all the time.
But you can do this virtually so nobody gets hurt, nobody gets
mad. So by providing both a simulator
and real world data sets and videos, enabling what they call
a self reinforcing development loop, developers train models on
a wide range of situations, test them in simulation, and
continuously improve the system in all of this.
Which is crazy. It's public.
You and I can check it out. Alpa SIM ALPASIM is on GitHub.
The data is on a hugging face. We can check it all out.
The barrier to entry for autonomous vehicle development
just drops significantly. Test like it has some absolute
killer competition. NVIDIA has planted their flag.
The technology that only a few companies had access to is
beginning to be available for everybody.
Now this is going to be a crowded race here.
Every vehicle manufacturer has access to this and why would
they spend years developing their own from here on out when
they can just plug in NVIDIA stuff and then plug in some
sensors, plug in their own cameras, plug in their own
stacks of other things. It seems like a no brainer to
me. They're going to be not the
Apple, but they're going to be the Android of vehicles.
They're going to make so much money.
They're going to be selling their cloud services, their
sensors, their chips, etcetera. This is going to be so much
money for NVIDIA. I can't wait to see what happens
in the future because one, I want to take a ride in this
thing. I want to see how great it
actually performs compared to a Tesla.
And two, just think about how easy it's going to be when you
need to go someplace and you don't actually have to own a
car. Any that's going to be great.
That's going to be 1 asset that doesn't depreciate when you
drive it off the lot. It's going to be democratization
of driving.