Exploring the Power of Kimi K2: Fast, Cheap, and Efficient Coding

--- type: transcript date: 2025-10-24 youtube_id: asamzJjPGS4 --- # Transcript: Exploring the Power of Kimi K2: Fast, Cheap, and Efficient Coding Two months ago, I built Open Lovable with Claude Sonnet. Then I switched to Kimmy K2, a model that's faster, cheaper, and outperforms on coding tasks as well as it being open source. In this video, I'm going to be showing you why exactly it's such a powerful model, as well as how you can get started. Now, what I wanted to do in this video is I wanted to show you how to set up Cloud Code with this new model. And additionally, I want to show you how I've been using Kimmy K2 within Openleable. In terms of the model that I most prefer for actually leveraging this platform is Kimmy K2. I've tried Sonnet 4, GPD5, and others, but I keep coming back to Kimmy K2 both because of the speed as well as the quality of the code generation that it has. Without further ado, let's dive in. If you haven't heard of Kimmy K2, so this was an open source model that the team over at Moonshot AI released at the start of the summer. And this took a lot of people by storm. A ton of people found this model very impressive. And the fact that it was open- source in addition to having very strong coding capabilities made it that much more interesting. Okay, so the first thing that I want to go over are the benchmarks of the model. This was a model that originally came out in July and it was already a very strong model in terms of open source models that were out there. This was the best model that I used for coding as well as agentic task. And what's exciting about this latest release this 0905 release is the agentic capabilities as well as things like the code development in particular the front-end development portion do perform very strong. When I was building open lovable originally I was using sonnet 4. I actually thought that was probably the best in terms of the inference speed as well as the actual coding capabilities for the model that was out there. But to my surprise, when I swapped in the Kimmy K2 model, it was faster. It was much cheaper than the entropic models and it was way faster because the thing with these models from Moonshot AI is you're going to be able to run them on different providers. Moonshot has their own inference solution. You can access their own API. The thing that's great with this being an open source model is you are going to be able to access it across a number of different providers. So you can access it from Moonshot themselves. You can also access this model on things like Grock as well as a number of different providers that are out there. Now to go over some of the specifics of the model. This is a state-of-the-art mixture of experts model. It has a total of a trillion parameters as well as 32 billion active parameters. Now, the key capabilities that they focused on with this model was its agent coding intelligence as well as its improved performance for a number of different tasks. One of them being front-end coding in particular and I definitely noticed that when I was developing open lovable for the original and when I ultimately switched to that 0905, I saw an even better increase building that out. Last but not least, the context window has also doubled from 128,000 tokens of contacts all the way up to 256,000. Now, just to quickly touch on some of the benchmarks, this is a substantial increase in just a couple months. It was already a strong model at 65.8 on Swebench verified. It's jumped up to 69.2, coming close to Claude for Sonnet in terms of its agent capabilities. And on terminal bench, it actually even outperforms in some scenarios claude for sonnet. We can also see a number of other benchmarks here that it either outperforms some of the open source alternatives or does come quite close to the anthropic series of models. And the thing with the anthropic models, the sonnet as well as opus models. These are some of the most popular models for developers. Now I want to show you how you can set up Kimik2905 within cloud code. First up, if you haven't tried cloud code, I definitely encourage it. you will have to have Node.js installed as a requirement. Once you have that, you can go ahead and paste in the installation step into the terminal. And then in terms of actually setting up the model within Cloud Code, what you can do is you can head on over to the platform.shot.ai console. You can generate an API key. And once you have that, I'll show you the steps to enable Cloud Code to actually build this and route your request to Moonshot AI rather than to Anthropic. Once you have cloud code installed, all that you need to run to actually set this up is you can set the anthropic o token to your moonshot API key. Once you've generated an API key, all that you need to do is set your authentication token as well as route the base URL to Moonshot AI as well as their anthropic endpoint and that will point the inference to actually use this latest model that they have from Kimmy for all of the requests instead of leveraging either Opus or Sonnet from Anthropic. And this is something that I don't think a lot of people realize is you don't necessarily need to use the models from Anthropic to use cloud code. Once you've added those environment variables, once we've run those, what we can do is if we run claude now, what we'll see within here is we'll have the base URL route now all of our queries to moonshot instead of anthropic. Now, what I've done is I've spun up a blank Nex.js template. And within here, what I'm going to do is I'm going to say I want to create a SAS landing page. I want to replace the homepage and I want to have all of the different component pieces. I want a pricing section, a hero section. I want an FAQ section, a functional header as well as footer. Make sure it looks good both on desktop as well as mobile. And let's have an overall modern theme. I want this to be black and white. I want the and I want the font to be relatively thin. And also make sure that all of these components are broken out into their own respective components files. Right off the bat, what we'll see is it's going to decompose this task into a number of different steps within here. It's going to create a modern SAS landing page with all of the components that I requested. We see it going through and it's executing all of those relevant commands to actually explore the current directory of different files that we have within our Nex.js project. So we see within here the first thing that it did is it listed out all of the different files and then it's reading through strategically some of the files that are relevant to what we're asking for. So we see it looking through the package, the layout as well as the page and the globals.css because we're having things that are going to be global potentially within the layout. We're also going to have things within the page within the app where all of the different components will live. And within here now we can see it wants to create a components directory. And I'm also going to specify to allow it to actually execute these commands autonomously. What this should do is it's going to create those components in their respective directories. By the end of this, we'll see what the initial generation has for us and what it can do completely autonomously. It's creating a header component and now it's going to work through all of those component pieces of what we have on a SAS landing page. Things like the pricing as well as the FAQs and footer just like I had asked for. Now I see that it is ready. If I just quickly go through what it has set up for us within the layout, we see that it has updated a new font for us. I asked for a relatively thin font. We can see it's made some changes to the overall global CSS file. We can see within the homepage here, it's removing that boiler plate. And we do see that it's adding in all of those respective component pieces within there. And here is what we have here. Right off the bat, we have SAS at the top. And that was one thing that I did put in actually with the dictation software. We have a really nice modern look and feel. We see in terms of front-end development, a very strong first generation. We have the pricing just like we had asked for. We also have our FAQ section where I can expand and collapse these. We have functional components. And then we also have a very respectable footer for what it has generated for us. Now, in terms of the front-end capabilities, I'm definitely very impressed with this. It followed all of our instructions. It also has a very good sort of nuance understanding of some of these component pieces. Now, as you get into it, it was able to decompose what we asked for in terms of what it needs to look for within our project. Now, in terms of a first generation, I am definitely quite impressed with this in terms of the front-end design capabilities, but also its actual agentic coding capabilities. Cuz if we just go through what it did here, essentially looked to list out all of the different files once it found that it was essentially a Nex.js JS application. It read through the key files that it needed to know about like the package layout, page, so on and so forth. And then once it knew the structure of the current project, it just went ahead and created all of these respective components in both the proper directories. It executed the relevant terminal commands and it created a coherent structure for what it ultimately generated for us on the right hand side here. Now, in terms of actually leveraging this with include code, the one nice thing with this is it is going to be quite a bit cheaper than the anthropic series of models. And in terms of its overall capabilities, like I said, I'll let you be the judge in terms of the front-end design portion, but it does perform quite well. And the thing to note with Cloud Code is it makes it really easy to add in various MCP servers for documentation. If you want to use something like context 7 or fire crawl to grab in all of the different relevant pieces of up-to-date information for whatever you're building, you can go ahead and do that and still leverage it with Kimmy K2. Now, I'm going to show you Kimmy K2 within OpenLovable V2. So, one of the new features that I added to OpenLovable V2 is the ability to have search terms. So, what you're going to be able to do is you can put in a search term. So, for instance, within this I put in and let's say I want to re-imagine this sort of dated site. I'm going to say I want to re-imagine the site in a neo brutalist theme. So what you can do is you can select of the different search option the site that you want to clone and reimagine. What I can do is I can click to apply and clone this and as soon as I click to do that what it's going to do is it's going to analyze the contents of the website. It's going to pull all of that context that we need leveraging fire crawl. And once we have all of that information, what it's going to do is it's going to generate all of those different respective files, put them in the right spot. Once we have all of those respective files, what it's going to do, similar to the cloud code process, is it's going to go and map out all of the different places that it needs to write these files to. And here we go. Here is what Kim K2 has generated for us. So, it has the neo brutalist theme just like we had asked for. It's kept the context of all of the different images. is. And if I just go through here, we have this overall sort of fun, modern look and feel to what was previously a very old and tired looking site. That is yet another option in terms of how you can try out this model. I'll also put a link to this within the description of the video. But otherwise, that's pretty much it for this video. I encourage you to check out Kimmy K2, try it out within Open Lovable, try it out within Cloud Code. It is a very impressive model both at front-end development as well as agented coding tasks. As someone who has built some of these code generation open source tools before, this is honestly the preferred model that I've had within open lovable since I actually started building it and from when I swapped out to Sonnet 4. It's faster, it's cheaper, it does very well at front-end design and it does follow instructions exceptionally well and for coding context, it does generate actually quite good code in my opinion. Last but not least, one thing that I do want to flag is Kimy's new okay computer mode. Now, what this mode allows you to do is to really leverage the power of K2 under the hood. Now, what you can do with this is quite vast. So, you're going to be able to create different mockups for websites, be able to create components for front-end design. You're going to be able to do things like upload up to a million rows of data where you're going to be able to effectively make these interactive different visualizations whether it's for company presentations or data visualization. You're going to be able to create mobile friendly applications. You're going to be able to upload all sorts of different data to this. And in addition to that, you're also going to be able to make even PowerPoint slides. But overall, it is just yet another demonstration in terms of how you can leverage the power of Kimmy K2 under the hood. So check it out and if you have any questions or comments, leave them within the comments section below. And if you found this video useful, please comment, share, and subscribe. Otherwise, until the next