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 GPT 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 Grok 4 .
6 61 .
So it ties it and it's much cheaper .
And then even on all of these other benchmarks ,
for example , the Code 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 .
Same thing with the Frontier Code .
It gets close to Fable 5 , beats GPT 5 .
6 .
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 Grok 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 Grok 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 Grok 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 .
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And what you see on screen right now is a racing game that Grok
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 .
6 it cost about 2 .
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 , Anthropic , 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 to performance 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 DeepSeek ,
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
3 .
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 DeepSeek 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 for today's video .
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