Grok 4.5 explained in 8min..

Grok 4.5 is the next frontier model released by SpaceX AI. But, unlike previous Grok 4 variants, the new Grok 4.5 model is actually based on a newly pre-trained V9 foundation model that is 1.5 trillion parameters in size, nearly three times bigger than the previous V8 base model. Now, the reason why this is worth mentioning is because when we have a newly pre-trained model, it typically requires training the model from scratch with a fresh batch of data. And we know that SpaceX recently acquired Cursor's parent company AnySphere back in June, and the amount of high-quality coding data that went towards the V9 base model opens up so much room for newer capabilities. And this is exactly what Elon tweeted on X, where Cursor data was supplemental to the new V9 foundation model's training. Another fact worth noting is the size of the model being 1.5 trillion parameter model, which is comparable to open models like Chimera 2.6, which is a 1 trillion parameter model, and Deep Seek V4 Pro, which is 1.6 parameter model. And despite that, Grok 4.5 pulls ahead in performance when you compare them against all open models, as you can see here. But, just a bit shy of state-of-the-art models like Fable 5 and GPT-5.6. But, what's crazy to think about when looking at this index from Artificial Analysis is that this entire section of models were all announced only in the short span of the past 30 days, except for Opus 4.8. Fable 5 was initially released on June 9, GPT-5.6 announced on June 26, and now we have the Grok 4.5 model, all within the past 30 days, which once again shows a brutal competition among frontier labs trying to stay ahead. The last time we had a performance leap like this was back in September 2024, when the first reasoning model O1 was released by OpenAI, as you can see. And it took the rest of the industry nearly 6 months to catch up, first by Deep Seek during the Deep Seek moment back in January 2025. And ever since, we had small increments here and there. And yet again, we have a new leap. But this time started by Anthropic with their Mythos and Fable model, and the rest of the industry like OpenAI and Grok are now catching up really fast. I'm not sure why this chart doesn't have GPT-5.6 Soul added here, but for reference, the 5.6 Soul should land right around here. So, we are undergoing yet another leap in model performance in how LLMs are progressing. Now, when we compare the Grok 4.5 model side by side against other state-of-the-art models like Fable 5, Opus 4.8, GPT-5.6 Soul, and hopefully Google's Gemini models soon, I hope. The first thing you might have noticed is just how cheap the model is in comparison. Pricing is just at $2 per million input tokens and $6 per million output tokens. Now, the phrase that always gets tossed around when it comes to pricing is subsidized plans. Most people don't use credits to buy API costs, but opt in to pay monthly subscription plan that subsidizes users to use their models. What's crazy about the Grok 4.5 model though is that Grok 4.5 API cost is comparable to a much lower tier models from other labs like Sonnet 5 from Anthropic, GPT-5.6 Lunar from OpenAI, and Gemini 3.5 Flash from Google, all lower tier models. They're essentially undercutting the entire closed labs when it comes to the cost of intelligence. Now, when we compare Grok 4.5 against open models, they're actually one of the most expensive models available out there. Looking at models like MiniMax M3, Kimmy K2.6, DeepSeek V4 Pro, GLM-5.2, and Qwen-3.7 Max, all noticeably cheaper except for Qwen-3.7 Max. So, really, Grok 4.5 is in this wedge not only in performance, but also in pricing where they are priced better than frontier labs in the US, but more expensive compared to open models while being more capable in intelligence than open models, but slightly below the frontier labs top performance. So, the next question here is usefulness. How useful is Grok 4.5 model? And what are its use cases? But first, quick word from Make sponsoring this video. Agents are what everyone is building today, but there's a huge technical gap when it comes to having your agent be more than just a chatbot. We want our agent to pull information from databases, make updates to spreadsheets, and update fields in the database. And we rely on MCP to handle all these things, but managing multiple MCPs and making sure they're all working together can get quite complicated. Make offers a super intuitive UI to build your own workflow that supports over 3,000 apps, as you can see from this drop-down list. From here, I can select my Superbase to connect to, and also my Google Sheets. And now, because these things are added as their own tool inside of Make, my agent can vote them through a unified MCP through Make on jobs that I give permissions to. As you can see, when I tell my agent to pull information from the database to collect all World Cup scores, it can do that. And I can also tell my agent to write to my Google Sheets all through Make. You can extend your agent through Make for free using 1-month pro subscription that allows 10,000 operations. Link in the description below. When we read through the release note for Grok 4.5, they're signaling that this model is perfect for coding use cases, for developing software, and office work for knowledge tasks. You can see in their demonstration of how Grok 4.5 one-shotted the solar system app that simulates our solar system in the super interactive way, where we have a planet's POV like this as they float around in space. But this is just their demonstration, so we got to pull up our sleeves and test it out ourselves. I'm using their own harness called Grok Built to start with, and I asked the model to put together a major data centers in the US in a visualized site. And I was surprised by just how fast the model actually got things done. It pulled together a lot of information about data centers, but also built the site with code in just a few minutes. And the site looks something like this, where it visually shows you a map of all major data centers in the US, and I can filter them by companies that are hosting them and go through each one by one. And I can also zoom into them as well. Pretty impressive for how quick it was able to get the job done. Now, to test their office task abilities, I pulled up a different harness since Grok 4.5 is also available on Cursor. So, I loaded up Cursor and picked the model Grok 4.5 from the drop-down. And I asked it to convert this website we just created into a Word file as a corporate briefing and also create a PowerPoint to do presentations on. And within just a minute or two again, you see that Grok was able to generate two extra files here, one for Word document and another for PowerPoint. The document written here shows a briefing outlining all data centers nicely organized and detailed. And the same thing for PowerPoint. Very simple and clean as I prompted specifically for Grok to follow. Now, beyond this, you can keep trying out the model and for me, I was testing something really technical until I ran out of credits. But my honest feedback is that the model is noticeably fast in output. And looking at their 85 tokens per second SLA, it might not seem all that impressive, especially in comparison to OpenAI's recent GPT 5.6 announcement running 750 tokens per second as an option, but I think the appeal to a model like this is using less tokens to get the job done, which is a different kind of speed. According to their report, they showed that Grok 4.5 solves the SweBench Pro benchmark using less tokens, where the model's average output tokens was up to 4.2 times less than Opus. All in all, Grok 4.5 is showing the industry that xAI they're trying to wedge themselves in the market when it comes to pricing and intelligence, but also being a serious competitor in the enterprise adoption of AI models given its smaller footprint in model size, their integration with cursor and their large compute availability. And according to Elon, they will be increasing their context window to 1 million context in just the next few days, which currently the model only offers up to 500,000 tokens.