So, Deepseek version 4 Pro is officially
out today. Now, you might be confused
because this model was technically out,
but it was in general availability, but
this is the official release, meaning
that they have trained the model a
little bit more and produced a stronger
version of the model that is available
today. Now, if I were to summarize
today's release in one simple sentence,
it is that the price to performance is
becoming a very, very important thing
because not only do we have a new model
from the Deepseek team, the SpaceX team
also dropped Grock 4.6 six. And both of
these models are competing with the best
Frontier Labs at a fraction of their
cost. Let's start with Gro 4.6. And one
thing I'm going to say is that I'm
genuinely surprised by the SpaceX team.
I'm not trying to glaze them or Elon
Musk or anything. I was just very
critical of this lab. In 2025, they
dropped Grog 4 and other models like
that, but I wasn't really, you know,
mind blown with their performance
because they're pretty they're pretty
subpar compared to any of the other labs
out there. But in 2026, it looks like
things have kind of changed a little
because Grock 4.5 was quite competitive
based off what it cost and Grock 4.6 is
actually not too bad. If we take a look
at the benchmarks, for example, if we
start with the artificial analysis
intelligence index, this model achieves
a 61 and Fable 5 is at 62. Now, what's
really important to remember is that
once again, this model is quite cheap
compared to Fable 5. This is about $2
per million input tokens and $6 per
million output tokens. In Fable 5 sits
at $10 per million input tokens and $50
per million output tokens. And this is
why you start to appreciate this release
a little bit more. It might not beat the
performance of the best models is
matching them. Even GBT 5.6 so which is
a pretty capable model and this is set
at max on the artificial analysis index.
This model achieves 61 and Grock 4.6 61.
So it ties it and it's much cheaper. And
then even on all of these other
benchmarks, for example, the GDP Val
one, it actually beats Fable 5, which is
at 1741. And then GPT 5.6, it's at 1728.
I'm not sure why they didn't choose Opus
5 as well, but I guess they wanted to
choose the quote unquote strongest model
lineup from each lab. And they chose
Fable 5 for Enthropic, which is fair.
And then Deep Software Engineering one,
which is a critical benchmark. This
model doesn't beat Fable 5 or GPT 5.6
six soul, but it gets close to it. It's
65.9 and Fable 5 sits at 70%. But if
you're getting results that are pretty
close and the model is five times
cheaper, I wouldn't be too disappointed
with this result. And then same thing
with Cursor Bench 3.2, the model
achieves 69.9%,
funny number. And Fable 5 sits at 70.5.
So once again, closer. And Grock 4.6
beats GPT 5.6 Soul. Same thing with the
Frontier Code. It gets close to Fable 5,
beats GPT 5.6 Soul. So yeah, this model
is actually available in cursor. So the
partnership with cursor or I guess the
acquisition has really helped SpaceX
make some strides in the AI space this
year and Grock build is something that
you know maybe not a lot of us have been
using so far but it's probably going to
be another platform like codeex or cloud
code that we start to use but obviously
cursor is quite strong as well. So you
have options available for you to use
them in both. And one thing to note is
that they're offering two times usage
inside Grock build and cursor for the
first week. So if you just want to try
it out, see what you feel about it, then
you know it might be worth trying it out
right now cuz you get double the usage
in the first week. Now if we were to
take a look at some of the outputs that
people have been generating with Grock
4.6, what we're looking at right now is
a Falcon 9 booster return sequence
simulation. And this was done in a
single HTML file. And as I said, if you
expected to get this type of output from
Grock in 2025, you would be kind of
surprised because you wouldn't expect
something like this to be generated with
Grock. But now it looks like we have to
start taking the Grock team a little bit
more serious because this output is
quite competitive. And obviously, we're
just looking at a simulation and we're
just basing it off of a visual
representation. But if the model is able
to produce something like this
consistently, then I would expect a lot
of people to start adopting Grock
because number one, it is cheaper than
the other labs at least at the moment
because we don't know if this pricing
strategy is going to be sustainable for
the SpaceX team in the long run. But at
least for now, their models are
definitely cheaper compared to the
others. And as I mentioned, this model
excelled at the artificial analysis
index. This model jumped to probably
number four model. It's tied to GPT 5.6
pretty much similar. So you could say
number three as well, but the models
before that are Fable 5 and Opus 5,
which are only above the model by about
a 1% or a 2% difference. So yeah, even
on this intelligence index, which if
you're not familiar with has nine
evaluations. So on all of these
evaluations, it's kind of matching
almost Fable 5 performance, which is
crazy to see. Before we continue, we
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miss out. And what you see on screen
right now is a racing game that Grock
4.6 build. And based off of this post,
the model took about 1 minute and it was
a fiveword prompt, which was a create a
simple racing game in HTML. So, if
you're able to generate something like
this easily using Grock 4.6, I think a
lot of people will be happy. And this is
a more detailed analysis of what it
costs to run GPT 5.6 6 on the artificial
analysis index and what it produced
meaning the output. Both of these models
if you remember scored 61 on the
artificial analysis index. Now to run
the whole test with GPT 5.6 it cost
about 2.8K and then with Grock 4.6 it
cost about 1.1Kish. And this tells you
that you're getting similar level of
performance at half the cost. So yeah,
this is a big release for the SpaceX
team because they just proved once again
that they are a lab that you seriously
start need to considering, especially in
2026. And I'm going to talk more about
Deep Seek version 4 Pro GA. But
basically what we're seeing today is
that both of these releases kind of
emphasize the fact that performance and
all above that is the price at what
you're getting for that performance is
becoming more and more important for all
users because we see many labs now
focusing on creating the best model at
the cheapest cost. Last year in 2025
most of the labs were just focused on I
would say creating the strongest model.
Yes, cost was important, but I think
most of the times the frontier labs,
meaning OpenAI, Enthropic, were kind of
more lenient on that fact because they
didn't have as strong of a competition.
Intelligent models that are maybe not
always ahead of OpenAI Enthropic, but
match their performance at a fraction of
the cost. So yes, price toerformance
ratio is becoming a critical I would say
indicator in 2026. Now, this is the
updated benchmark chart after the
release of the new model. And one thing
you'll see across the board is that it
matches the top level performance of
many of the models. The one thing
interesting over here is that they
haven't put Opus 5 here for some reason.
There is Fable 5 here that we can
compare this model against. But one
thing you'll notice is that Deep Seek,
remember this model costs 43.5 cents per
million input tokens and 87 cents per
million output tokens. While the other
models all over here are way more
expensive than that. So the first thing
if you look at terminal bench 2.1 the
model scores 87.9.
The older version of the model was 72.1
and the flash version which we got last
week was 82.7. And what's crazy is that
Fable 5 is 88. Yes, 88. So this model is
only.1% behind Fable 5. And then on the
Cyber Gym, which is Cyber Security, the
model actually beats Fable 5. Fable 5
sits at 83.1 while Deepseek version 4
Pro, the new one that we got today, is
at 83.3. Now, if this tells you
something is that this model is once
again really geared at cyber security.
We saw the Flash model also be geared
towards cyber security and becoming a
model that was quite capable in that
area. And we're seeing the same thing
today with the new version 4 Pro which
sits at 83.3 outperforming Fable 5 on
the benchmark. On deep software
engineering, this model is not beating
Fable 5 because Fable 5 sits at 70, but
the model achieves 62.7 which is ahead
of GLM 5.2 and a bit behind Kimmy K3
which sits at 67.5.
But one thing again, this is a big jump
compared to the preview version of the
model which was at 12.8. So yeah, they
have really trained this model and they
have improved it on the back end because
we can clearly see in this deep software
engineering benchmark. And there's a
couple of other benchmarks, but one key
benchmark that this model excels at is
the automation bench where the model
achieves 31.8 and Fable 5 29.1. So once
again, the model outperforms Fable 5.
Now this is a fraction of the cost as I
mentioned. This is 43 cents and 87 for
input and output respectively versus
Fable 5 which is at $10.50.
So yes, if we look at the terminal bench
for example, we are seeing this model
achieve a result which is 0.1 behind the
best model out there Fable 5 and the
pricing is insane to look at $43 versus
$10 87 versus $50 per million input
tokens. So when we turn that into a
fraction, this model is 57 times
cheaper. And earlier last week, I think
I made a video about how DeepSeek
version 4 Pro was going to achieve a
result like this because there was a
investor report that leaked. And when I
saw the pricing where it said that it
was going to match Fable 5 or even
outperform it and be at 57 times cheaper
per cost. When I was reading the
investor report, I didn't really believe
it. But today, it is proven because at
least on the benchmark so far, yes, I'm
just saying the benchmarks, we are
seeing similar level performance. Now,
if this model actually performs like
that in production, it's a little too
early to tell yet. We still would have
to give it a couple of weeks and see how
it's performing in the long run because
sometimes on the release day the models
perform quite good, but over time they
kind of deteriorate in their quality.
So, we hope DeepS doesn't do that.
Historically, they haven't done that,
but let's just see. Just going to put it
out there because right now we're basing
this off of benchmarks. But that's it
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