So, looks like we just got flashed by
Google DeepMind [music] once again
because they just dropped Gemini 3.7
Flash today. Yes, their newest model,
which is once again a Flash model, is
here. And this is only after 3 weeks
since Gemini 3.6 Flash. And what they
are saying is that Gemini 3.7 Flash is
their most intelligent workhorse model.
And this is coming 3 weeks after 3.6 six
flash because of developer feedback and
algorithmic innovations. And that is why
they're saying the Gemini 3.7 Flash
model is, you know, out with so much
improvement cuz if we take a look at the
benchmarks, this model is way better
than the Gemini 3.6 Flash. But I think
this is also because we know internally
that they're planning on cancelelling
Gemini 3.5 Pro completely and working on
Gemini 4 at the moment. So maybe the
improvements they made with the Pro
model that they're not going to be
dropping anymore. Maybe they repackaged
it as a flash model because this model
is better than 3.6 and if the timeline
is three weeks plus they're planning on
cancelling the 3.5 Pro, it's quite
likely that is the case. We'll just
ignore that and put that into the side.
We don't know when we're getting a new
Pro model from the Google Deep Mind
team, but this model across many of the
benchmarks we will see that yes, it is
stronger than the 3.6 Flash model. For
example, when it comes to code quality,
production code quality, the model is
producing 43.6%
versus the flash model 34.4%.
And then Sonet 5 is at 42.7%
and the Terra model is at 41.3%.
So, one thing to remember, since this is
a flash model, you're not going to see
them compare this to Opus 5 or any of
the other stronger models. The reason
being cuz this is not their strongest
tier. and the 3.1 Pro model when they
finally decide to upgrade it to Gemini 4
Pro, then we'll see it being compared to
Opus 5 or GPT 5.6 Soul. But anyways, we
can see that this model is an
improvement from 3.6 Flash and I would
say that's basically the biggest result
or the biggest update that we saw with
the new model because it does not really
like change up things a lot is still
like not becoming the number one model
or the number one flash model. Even on
some benchmarks, Deepseek version 4
flash is actually cheaper and more
intelligent than this model. But let's
just take a look at the benchmarks that
they have published. On Long Horizon
software engineering, this model is a
little bit behind GPT 5.6 Terra, which
sits at 69.6%
and then 65.3% is the Flash model. The
older Flash model 3.6 sits at 48.6%.
Sonic 5 sits at 53.8% 8%. And the new
player that is finally being included on
benchmarks, which even the Google
DeepMind team is considering with their
launch, is Muse Spark 1.2, which is
sitting at 54.9%.
So, welcome Meta to the benchmark charts
because now we're starting to see it
appear on more and more benchmarks. And
if we also take a look at web
development, this model is getting a ELO
score of 1588 versus their old model is
1538. So, not a crazy difference, but
compared to everything else out there,
this is number one. When I say
everything else out there, once again,
compared to all the mid-tier models,
this is beating all of them when it
comes to web development. Now, this
model is probably going to be used in
enterprises a lot just because of
Google's footprint in the enterprise
space, but we are seeing this model
achieve on the automation bench 30.4%.
And GPT 5.6 Terra sits at 23.6%.
So, yes, this model is stronger than the
other Flash models out there, but as I
said, they haven't included Deepseek
version for Flash because if they do, in
some areas, that model is actually quite
better than the 3.7 Flash model. Before
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Thank you once again for Arcade for
sponsoring today's video. Now, let's get
back into the video. Now, one thing to
note is that the Gemini 3.7 Flash model
through the end of this year, so end of
2026, they have a cheap pricing model
that they're placing on the model. 75
per 1 million input tokens and $3.75 for
1 million output tokens. So, it's a
competitive price, but this is only for
the next 6 months. Because after those
six months are done, the model's pricing
is actually, you know, a little bit more
expensive. And now they show it at the
bottom over here, you can see that after
starting January of 2027, it will become
$1.50 per input and $7.50 per output. So
yeah, it's still cheap compared to the
other frontier labs, but it's not as
cheap as, for example, MU Spark when the
pricing is updated or even the Deepsee
version for Flash. But across these
benchmarks, we can see that this model
is better in many areas that they
highlighted at the top. But then they
also have some other areas like long
video understanding, which this model
excels at 85.4% versus 78.9%
for the Terra model. And then the old
model was also pretty good at that,
84.2%.
Then long context performance the model
is at 97% and this model the GPT 6 Terra
one it sits at 93.5%.
So yeah this model in summary it is
better so it's not all negative but it's
not all like you know that positive
where you are super excited for Google
Deep Mind because as I said they're
probably still holding off their biggest
release for Gemini 4 lineup. Now, one
thing people might have missed in their
charts because these charts sometimes
are so messy to read and understand, but
the 3.7 flash is worse than GPT 5.6
Luna, which is the model over here,
which is achieving a higher score on
this benchmark deepware engineering for
about three times the cost. So, yeah,
this is kind of interesting because
yeah, the cost for Gemini 3.7 Flash is a
little bit more than what it looks like.
Now, some people are a little bit upset
and they're like, "Oh, disgraceful.
Google left out soul, opus, and fable
because Google is incredibly behind. But
I think one thing we got to remember,
guys, is that this model is a flash
model. It's not trying to be a pro model
or it's not trying to compete with Opus
or Soul or Fable 5 level models yet.
That is probably going to be Gemini 4.
So when Gemini 4 comes out, then I think
it's okay for us to criticize them if
they don't include Soul, Opus, and Fable
in their benchmark charts because for
now, I think what they have done is
pretty accurate. One lab that I would
have liked to see or one model for
example I would have liked to see on
that chart would be Deepseek version 4
Flash because that would kind of spoil
their release because that model is way
cheaper compared to the Gemini 3.7 flash
model lineup. Now this model jumped from
number 19 to 8 on the web development
area and we see it over here now and
couple of models that are ahead of it
are Opus 5 obviously Kim K3 Quinn 3.8
Max Cloud Opus 5 Gro 4.6 6, which is a
model that came yesterday, which was a
big win for SpaceX, Fable 5, and 5.6.
Soul. So, yeah, this model is trying to
compete in the web development, but it's
still behind all of these models, which
is, you know, expected cuz it's a flash
model. It's not really a pro model.
Today, OpenAI has also launched a weight
list for 5.6 so ultra fast mode. Now,
this is possible because of the fast
chips that they have access to now
through Cabus and GPT 5.6 6o with this
chip kind of running it is able to
achieve an ultra fast mode that
generates up to 750 output tokens per
second which is about 14 times faster
than the standard mode. So we're getting
a really fast version of GPT 5.6 so now
this is supposed to be used for live or
near production workloads like you know
real-time voice support commerce what
this allows GPT 5.6 six soul to do is
kind of be really fast in critical
situations when people might be
interacting with the AI agent like
financial research security response
support I think is going to be a big
area where this new ultraast mode will
be kind of implemented business and
developer agents maybe yeah but I think
like support or near production
workloads like real-time voice I see
this model really excelling at that and
obviously this is still a weightless
mode we don't know how many people are
going to get access to this, how
successful it is or what the pricing is.
I don't know if the pricing has changed
because there's no information in their
actual, you know, blog post. But as I
mentioned, couple of areas where they
mentioned that this is going to be
really important. Customer support and
voice, commerce, live research and
experimentation, financial research and
security, incident response and
reliability. But yeah, I think this
partnership is going to be important for
OpenAI going forward. But as I said, 14
times the speed. What does that mean for
cost? We don't know yet. But that's it
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