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So looks like we just got flashed by Google DeepMind once again because they just dropped

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Gemini 3.7 flash today. Yes, their newest model, which is once again a flash model, is here.

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And this is only after three weeks since Gemini 3.6 flash. And what they are saying is that Gemini

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3.7 flash is their most intelligent workhorse model. And this is coming three weeks after 3.6

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flash because of developer feedback and algorithmic innovations and that is why they're saying that

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gemini 3.7 flash model is you know out with so much improvement because if you take a look at

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the benchmarks this model is way better than a gemini 3.6 flash but i think this is also because

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we know internally that they're planning on canceling gemini 3.5 pro completely and working

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on gemini 4 at the moment so maybe the improvements they made with the pro model that they're not

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going to be dropping anymore maybe they repackaged it as a flash model because this model is better

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than 3.6 and if the timeline is three weeks plus they're planning on canceling the 3.5 pro it's

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quite likely that is the case we'll just ignore that and put that into the side we don't know

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when we're getting a new pro model from the google deep mine team but this model across many of the

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benchmarks we will see that yes it is stronger than the 3.6 flash model for example when it comes

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to code quality production code quality the model is producing 43.6 percent versus the flash model

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34.4 percent and then sonnet 5 is at 42.7 percent and the terra model is at 41.3 percent so one thing

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to remember since this is a flash model you're not going to see them compare this to opus 5 or any of

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the other stronger models the reason being because this is not their strongest tier and the 3.1 pro

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model when they finally decide to upgrade it to Gemini 4 Pro probably then we'll see it being

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compared to Opus 5 or GPT 5.6 Soul but anyways we can see that this model is an improvement from

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3.6 Flash and I would say that's basically the biggest result or the biggest update that we saw

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with the new model because it does not really like change up things a lot it's still like not

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becoming the number one model or the number one Flash model even on some benchmarks DeepSeek

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version for flash it's actually cheaper and more intelligent than this model but let's just take a

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look at the benchmarks that they have published on long horizon software engineering this model

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is a little bit behind gpd 5.6 tera which sits at 69.6 percent and then 65.3 percent is the flash

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model the older flash model 3.6 sits at 48.6 percent sonnet 5 sits at 53.8 percent and the

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new player that is finally being included on benchmarks which even the google deep mine team

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is considering with their launch is musepark 1.2 which is sitting at 54.9 so welcome meta to the

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benchmark charts because now we're starting to see it appear on more and more benchmarks and if we

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also take a look at web development this model is getting an elo score of 1588 versus their old

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model is 1538 so not a crazy difference but compared to everything else out there this is

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number one. When I say everything else out there, once again, compared to all the mid-tier models,

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this is beating all of them when it comes to web development. Now, this model is probably going to

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be used in enterprises a lot just because of Google's footprint in the enterprise space.

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But we are seeing this model achieve on the automation bench 30.4%. And GPT 5.6 Terra sits

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at 23.6%. So yes, this model is stronger than the other Flash models out there. But as I said,

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they haven't included DeepSeq version for Flash because if they do, in some areas that model is

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actually quite better than the 3.7 Flash model. Before we continue, if you're building AI agents

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The models are smart enough. Your agent can figure out exactly what needs to happen in your email,

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your Slack, your CRM. It just can't go in and do it. And the reason isn't intelligence, it's

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Arcade has thousands of them already built for Gmail, Google Drive, Slack, Notion, Salesforce,

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most of the apps people already work in, and they are built specifically for AI to use,

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so the agent gets it right the first time instead of guessing and failing and retrying.

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It also keeps a record of everything, what the agent did for who and where,

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which matters a lot the moment other people start using the thing you built.

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And it works with whatever you're already using. Any model, any framework, cloud, cursor, chat GPT,

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you're giving it a place where it can safely take real actions in real apps. It's free to start and

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the link is in the description. Thank you once again for Arcade for sponsoring today's video.

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Now let's get back into the video. Now one thing to note is that the Gemini 3.7 flash model through

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the end of this year so end of 2026 they have a cheap pricing model that they're placing on the

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model 75 cents per 1 million input tokens and 3 dollars and 75 cents for 1 million output tokens

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so it's a competitive price but this is only for the next six months because after those six months

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are done the model's pricing is actually you know a little bit more expensive and now they show it

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at the bottom over here you can see that after starting January of 2027 it will become a dollar

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and 50 per input and seven dollars and 50 per output so yeah it's still cheap compared to the

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other frontier labs but it's not as cheap as for example muse spark when the pricing is updated

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or even deep seek version for flash but across these benchmarks we can see that this model

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is better in many areas that they highlighted at the top but then they also have some other areas

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like long video understanding which this model excels at 85.4% versus 78.9% for the Terra model

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and then the old model was also pretty good at that 84.2%. Then long context performance the

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model is at 97% and this model the GPT-6 Terra one it sits at 93.5%. So yeah this model in summary

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it is better so it's not all negative but it's not all like you know that positive where you are

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super excited for Google DeepMind because as I said they're probably still holding off their

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biggest release for Gemini 4 lineup. Now one thing people might have missed in their charts because

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these charts sometimes are so messy to read and understand but the 3.7 flash is worse than GPT 5.6

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Luna which is the model over here which is achieving a higher score on this benchmark

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deep software engineering for about three times the cost. So yeah this is kind of interesting

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because yeah the cost for gemini 3.7 flash is a little bit more than what it looks like

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now some people are a little bit upset and they're like oh disgraceful google left out

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so opus and fable because google is incredibly behind but i think one thing we got to remember

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guys is that this model is a flash model

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to be a pro model or it's not trying to compete with opus or soul or fable five level models yet

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that is probably going to be gemini 4 so when gemini 4 comes out then i think it's okay for

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us to criticize them if they don't include Sol, Opus, and Fable in their benchmark charts because

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for now I think what they have done is pretty accurate. One lab that I would have liked to see

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or one model for example I would have liked to see on that chart would be DeepSeq version 4 Flash

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because that would kind of spoil their release because that model is way cheaper compared to

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the Gemini 3.7 Flash model lineup. Now this model jumped from number 19 to 8 on the web development

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area and we see it over here now and a couple of models that are ahead of it are Opus 5 obviously,

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Kimi K3, Quen 3.8 Max, Cloud Opus 5, Grok 4.6 which is a model that came yesterday which was a big win

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for SpaceX, Fable 5 and 5.6 Sol. So yeah this model is trying to compete in the web development

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but it's still behind all of these models which is you know expected because it's a flash model

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it's not really a pro model. Today OpenAI has also launched a waitlist for 5.6 SOL ultra fast mode.

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Now this is possible because of the fast chips that they have access to now through Cerebris

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and GPT 5.6 SOL with this chip kind of running it is able to achieve an ultra fast mode that

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generates up to 750 output tokens per second which is about 14 times faster than the standard mode.

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So we're getting a really fast version of GPT 5.6 Soul. And now this is supposed to be used for

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live or near production workloads like, you know, real-time voice, support, commerce.

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What this allows GPT 5.6 Soul to do is kind of be really fast in critical situations when people

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might be interacting with the AI agent, like financial research, security response, support,

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I think is going to be a big area where this new ultra fast mode will be kind of implemented.

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business and developer agents maybe yeah but i think like support or near production workloads

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like real-time voice i see this model really excelling at that and obviously this is still

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a waitlist mode we don't know how many people are going to get access to this how successful it is

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or what the pricing is i don't know if the pricing has changed because there's no information in their

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actual you know blog post but as i mentioned a couple of areas where they mentioned that this

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is going to be really important customer support and voice commerce live research and experimentation

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financial research and security incident response and reliability but yeah i think this partnership

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is going to be important for open ai going forward but as i said 14 times the speed what does that

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mean for cost we don't know yet but that's it for today's video make sure you guys are subscribed

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Until then, I'll see you guys in the next video.