Why is Everyone OBSESSED With The New Kimi K2.5 AI Model

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Transcript

00:00:00Wait, I just noticed.
00:00:01The report is based on publicly available information as of January 2025.
00:00:06Oh no, oh no, 2025, no, that's not what I asked for.
00:00:15Moonshot AI has released their newest AI model, Kimi K 2.5, and it's been all the rage this
00:00:22week around the internet.
00:00:24Some people are even going as far as saying this might be their favorite model yet.
00:00:29So naturally I had to test it out to see what the fuss is all about and determine if this
00:00:34really is something fresh or is it just another model that's hyped up by flashing marketing.
00:00:39So that's what we're going to find out in today's video.
00:00:42It's going to be a lot of fun, so let's dive into it.
00:00:49So Kimi K 2.5 is the latest open source model developed by a Chinese company called Moonshot
00:00:55AI.
00:00:56Just six months ago Richard already covered K2 in great detail and today we are back and
00:01:01we're looking at what's new in K2.5.
00:01:05So what's the big deal about this model?
00:01:06How is it different from all other thousand new models out there coming out almost daily?
00:01:12Well there's two things.
00:01:13First of all it claims to be really good at vision and coding.
00:01:17It even goes as far as labeling themselves as open source SOTA.
00:01:21SOTA.
00:01:22Do you realize what that means?
00:01:24Actually I had to look it up myself what it means I don't actually know.
00:01:27Oh okay so it means state of the art.
00:01:30Okay well today I learned.
00:01:32So anyway it is full on state of the art on agentic benchmarks and vision and coding.
00:01:37And the second thing that stands out in this model is that it has a new functionality called
00:01:42Agent Swarm.
00:01:44Where it is capable of spinning up up to hundred subagents and 1,500 tool calls and run them
00:01:51concurrently resulting in a 4.5 times faster performance.
00:01:55For this model they used a new training method called parallel agent reinforcement learning
00:02:00or PARL.
00:02:01And this means that the model can self-direct the whole agent swarm by creating a trainable
00:02:06orchestrator agent which is basically running the show by decomposing tasks into paralyzable
00:02:12subtasks and is keeping an eye on all of these agents to ensure that the whole operation doesn't
00:02:18fall into a serial collapse which tend to happen with these multi-agent workflows.
00:02:23The way they solved this is by giving each subagent rewards at separate critical step
00:02:28stages and this whole system lets k 2.5 achieve noticeable performance gains.
00:02:34So we're definitely going to test it out.
00:02:35Now I'm not going to go into too much detail about all of the different benchmarks because
00:02:40honestly every video I see now is always praising these numbers and I don't even think we can
00:02:44trust these numbers anymore to be honest.
00:02:47They can't even line up their benchmark graphics properly, come on.
00:02:51So instead I'm going to be focusing on the two things they claim this model seems to be
00:02:55good at.
00:02:56Vision and coding and the new agent swarm functionality.
00:03:00So let's put it up for a test.
00:03:02They've also got their own CLI tool called Kimi CLI.
00:03:06So that's what I'm going to be using today to conduct my tests.
00:03:09So one of the most impressive features they claim to have is the ability to take a video
00:03:13recording of a UX of a particular website and replicate that in code.
00:03:19That's pretty impressive.
00:03:20So to test it out, I made a video recording of Apple's iPad Air product page with all their
00:03:25fancy animations and transitions.
00:03:28And I created a folder that contains only the file of this recording.
00:03:32And now I'm going to prompt k 2.5 to make a promotional website for the iPad Air product
00:03:38based on this video.
00:03:39And before executing shell commands, it will ask if we want to allow it, so I'll allow it
00:03:44for this session.
00:03:46And it's now running.
00:03:48And this is interesting.
00:03:49It detected that the file was too large.
00:03:51So it went ahead and used FFmpeg to compress it on its own.
00:03:56And I was really curious to know how does this model process and understand a video file.
00:04:01It turns out that it takes the video file and once again, it's using FFmpeg to extract key
00:04:06frames from the video to use as visual aid for building the website.
00:04:11So it took the model roughly five and a half minutes to finish the task.
00:04:15So it's not the fastest model out there for sure.
00:04:18And mind you, I am using their own API's to call the model, not a local version.
00:04:23But anyway, once that is done, we can see here that it gives us a detailed overview of what
00:04:28it did.
00:04:29So now let's view the site itself.
00:04:30Oh, wow.
00:04:31Look at that.
00:04:32We nailed the whole Apple design aesthetic and it even created this 3D floating iPad in
00:04:38the middle.
00:04:39And it seems to be responding to mouse movements as well.
00:04:42That's pretty cool.
00:04:43Then we get this nice carousel section with different windows, but unfortunately it does
00:04:48not respond when I click on the dots, but it's still quite elegant.
00:04:52Then we get another section with some animations.
00:04:55Oh, and here we actually get a navigatable carousel with different designs.
00:05:00That's pretty cool.
00:05:01And then we get a couple of more sections, which all feel very similar to Apple's aesthetic.
00:05:06Honestly, this is pretty good.
00:05:07The fact that it was able to produce a nice looking website with all these animations just
00:05:12from a reference video and a short prompt is kind of cool.
00:05:16All right.
00:05:17But Apple is a well-known brand.
00:05:18I'm sure the design aesthetic is definitely part of their model's training data.
00:05:23So this is probably a straightforward task for the model.
00:05:26Now let's try something more interesting and a little bit quirky.
00:05:29I've created another folder with a single image of Mr. Burns from the Simpsons.
00:05:34Let's see how creative Kimmy K 2.5 can get.
00:05:37I've added this prompt, Mr. Burns is running for president.
00:05:40I want you to create a presidential campaign website for Mr. Burns, which includes his policies
00:05:45and political agenda based on this character's traits and motivation.
00:05:49Let's see how that does.
00:05:51Once it starts the reasoning process, we can see how it thinks about the design.
00:05:55The asset is clear.
00:05:56Montgomery Burns in his signature dark green suit and peach tie.
00:06:01This is the key visual reference for the campaign's aesthetic.
00:06:05Pretty cool.
00:06:06And this section actually took even longer to finish.
00:06:08This was around six minutes in total.
00:06:11But now that that's done, again, we see a detailed overview of what was produced and we can see
00:06:16here it added a vision section, a policy section, promotional materials, et cetera.
00:06:22And look at that.
00:06:23It even added a hidden Easter egg just for fun.
00:06:26Now that is super cool.
00:06:27Now let's see how the website looks.
00:06:29Wow.
00:06:30Look at that.
00:06:31Excellence in governance.
00:06:33I'm making this country great again for me.
00:06:36Oh, and there's a little nuclear button over there.
00:06:40What happens when I click it?
00:06:41Smithers gave me a coffee.
00:06:43That's cool.
00:06:44And there's even a detailed about page.
00:06:46And then there's prosperity.
00:06:49And the animations are so slick.
00:06:50Wow.
00:06:51So I guess Kimmy K 2.5 really knows how to create punchy graphics.
00:06:55It's obviously a lot better than all of those purplish slop designs that we've seen other
00:07:01models produce.
00:07:02And look at that.
00:07:04Policies for the elite.
00:07:05Oh, my God.
00:07:06There's so many good cheeky jokes here.
00:07:08That's amazing.
00:07:10Health care vouchers redeemable only at burns medical centers.
00:07:14Organ transplant waiting lists sorted by net wealth.
00:07:18Border wall made of gold.
00:07:21What are people saying?
00:07:22OK, here we get some Simpsons character quotes and the contact form and the campaign donation
00:07:29page.
00:07:30It even added a merch shop.
00:07:31OK, but that section is coming soon.
00:07:33Yeah, because this is a static HTML page.
00:07:35All right.
00:07:36Now I want to trigger that Easter egg.
00:07:38How do I do that?
00:07:39Konami code says I have to input the Konami code.
00:07:43What is a Konami code?
00:07:45Oh, OK.
00:07:46The Konami code is a famous video game cheat code.
00:07:49Wow.
00:07:50I didn't know this.
00:07:51Once again, today I learned.
00:07:52So it's up, up, down, down, left, right, left, right, A, B. Oh, OK.
00:07:58There we go.
00:07:59We now get the big ha ha ha text over the page and the slogan turns to excellent.
00:08:06That's pretty cute.
00:08:07But honestly, there are so many cool nuggets here that I'm just going to leave a link in
00:08:10the description for this home page so you can check it out for yourself later.
00:08:14The Simpsons fans might really appreciate this.
00:08:17This is really impressive, honestly.
00:08:19I didn't expect it to create such a fun website from just a single image and a short text prompt.
00:08:24All right.
00:08:25But now I want to try the agent swarm function everybody's been raving about.
00:08:29So looking at their own examples, apparently the swarm feature is very good for tasks like
00:08:33gathering research for a certain topic or any action, really, where you want a multi-threaded
00:08:39approach.
00:08:40But to test out this feature in all of its glory, it's best to use the official Kimi page
00:08:46and run it in their chatbot because they have also added a bunch of cool visual elements
00:08:50and animations that really makes the swarm process look very cool.
00:08:54You'll see that in a second.
00:08:56So for this test, I'm going to ask the agent swarm to gather as much information as it can
00:09:00about different models, which ones are the most used, and I'll ask K2.5 to gather all
00:09:06this information and consolidate it in a well formatted PDF document.
00:09:10And also if you do want the model to use the swarm, it is useful to ask it to do so because
00:09:16in one of my previous tests, I asked it to do a task and K2.5 concluded on its own that
00:09:23it didn't need to employ the swarm and gave me back some token credits.
00:09:27So if you really want to activate the swarm, just be sure to let it know.
00:09:31All right.
00:09:32So let's launch our task.
00:09:33And as soon as it starts, we can see these cool animations Kimi has on their chatbot interface.
00:09:39And this is honestly something that I've noticed Moonshot AI is very good at.
00:09:43They really excel at having a very playful, very gamified user experience, which kind
00:09:49of makes the whole process of using their tools much more fun.
00:09:52And again, Kimi is being cheeky here about the whole process as the model assigns the
00:09:57agents.
00:09:58And it even gives ID badges to each of them.
00:10:01And we can also track their task completion statuses in real time.
00:10:05And as the agents are completing the tasks, we can also follow their progress on the main
00:10:10window.
00:10:11We can see the web pages they are visiting and the code that they are producing.
00:10:15And at this point, you can also place your bets as to which agent will complete its task
00:10:20the fastest.
00:10:21Once the agent completes the task, you can see a little bubble pop up above their avatar.
00:10:26So roughly 10 and a half minutes later, my swarm has finished the given task and we get
00:10:31this PDF document as a result.
00:10:33It appears that there's there's a text here, but I can't quite seem to see it.
00:10:39OK, so I had to copy paste it somewhere to understand it.
00:10:43OK, so it says coding models, comparative analysis.
00:10:46OK, OK.
00:10:47Well, very bad design choice right from the start.
00:10:50But OK, let's let's not jump to conclusions.
00:10:53Let's look at the rest of the report.
00:10:55OK, we have an executive summary here.
00:10:58Major findings.
00:10:59Eighty one percent of devs use or plan to use AI.
00:11:03Fifty nine percent of devs run three AI tools in parallel.
00:11:06OK, OK, interesting.
00:11:08And we see here that Claude Code Opus 4.5 dominates the charts.
00:11:13And then we see market trends here.
00:11:16Forty six percent of devs actively distrusts AI outputs.
00:11:20And wow, this is surprising.
00:11:22GitHub copilot is the market leader with 42 percent of market share.
00:11:26Wow.
00:11:27Llama for Scout seems to have the largest context window with 10 million tokens.
00:11:31That is pretty impressive.
00:11:32OK, here it comes.
00:11:33The juicy parts.
00:11:34Key takeaways.
00:11:35OK, let's see.
00:11:36No single winner.
00:11:37Oh, come on.
00:11:39How lame.
00:11:41Forty five percent of AI generated code has vulnerabilities.
00:11:43Yeah, that is something to worry about for sure.
00:11:46Wait, I just noticed the report is based on publicly available information as of January
00:11:52twenty twenty five.
00:11:54Oh, no.
00:11:56Oh, no.
00:11:57Twenty twenty five.
00:11:59No, that's not what I asked for.
00:12:02I specifically asked it for information about the currently most used models currently.
00:12:09Why didn't you use data from January twenty twenty six?
00:12:14You're absolutely right.
00:12:15I should have researched data from twenty twenty five and January twenty twenty six.
00:12:21Typical LLM behavior.
00:12:23I am very disappointed in you, Kimi.
00:12:25I just wasted a bunch of tokens and 10 minutes of my time for outdated information.
00:12:30Oh, well.
00:12:31So there you have it.
00:12:32That is Kimi K2.5.
00:12:35Despite my utter disappointment in its ability to follow orders in the last test, I still
00:12:40think it's a pretty good model.
00:12:42I wouldn't say it's groundbreaking or state of the art, but it does have its upsides.
00:12:47I would certainly recommend it if you want to make a truly beautiful website, you know,
00:12:51something that you can display on awards dot com.
00:12:55Then I would definitely go with K2.5 opposed to one of the Claude Code models, for instance.
00:13:01And I got to be honest, the swarm feature looks very cool and it's definitely fun to
00:13:06use.
00:13:07But did you know that you can get the same feature using Claude Code?
00:13:10Richard just did a great video exploring that topic, so be sure to check that video out as
00:13:14well.
00:13:15And folks, if you found this video useful or at least entertaining, then let me know by
00:13:19smashing that like button underneath the video.
00:13:22And also be sure to subscribe to our channel so you don't miss out on any of our future
00:13:26technical breakdown videos.
00:13:28This has been Andris from Better Stack and I will see you in the next videos.

Key Takeaway

Kimi K2.5 excels at creating high-quality, aesthetically pleasing web designs from visual prompts through its unique Agent Swarm architecture, though it remains prone to typical LLM temporal hallucinations.

Highlights

Introduction of Kimi K2.5, a new open-source model from Moonshot AI claiming state-of-the-art performance in vision and coding.

The 'Agent Swarm' feature allows the model to orchestrate up to 100 sub-agents and 1,500 tool calls concurrently using the PARL training method.

Successful demonstration of vision-to-code capabilities by recreating a complex Apple product page and a creative Mr. Burns campaign site.

The model includes a highly gamified user interface with visual 'ID badges' and progress trackers for sub-agents.

Critical evaluation of a data retrieval error where the model provided outdated information from 2025 despite a request for current 2026 data.

Comparison with competitors like Claude Code, highlighting Kimi's superior aesthetic design but noting reliability issues in multi-agent workflows.

Timeline

Introduction to Kimi K2.5 and Moonshot AI

The video begins with a teaser of a data error before introducing Kimi K2.5, the latest release from the Chinese company Moonshot AI. The presenter notes that the model has generated significant hype online, leading to a deep-dive test to separate marketing from reality. It is positioned as a major update to the previous K2 model covered just six months prior. This section sets the stage for a critical analysis of whether the model is truly 'fresh' or just another hyped product. The speaker emphasizes the importance of verifying claims in a saturated AI market.

Technical Innovation: Agent Swarm and PARL

The speaker explains the core technical advantages of Kimi K2.5, specifically its focus on vision, coding, and agentic benchmarks. The standout feature is 'Agent Swarm,' which uses Parallel Agent Reinforcement Learning (PARL) to run up to 100 sub-agents simultaneously. This system employs a trainable orchestrator to decompose tasks and prevent 'serial collapse' by rewarding agents at critical step stages. The presenter expresses skepticism toward standard benchmarks, preferring to test real-world functionality instead. This technical context is crucial for understanding how Kimi achieves its claimed 4.5 times faster performance.

Vision-to-Code Test: Replicating Apple's UX

Using the Kimi CLI tool, the presenter tests the model's ability to recreate a website from a screen recording of Apple's iPad Air page. Kimi automatically uses FFmpeg to compress the video and extract key frames for visual analysis before generating the code. After roughly five and a half minutes, the model produces a high-fidelity site featuring 3D elements and responsive animations. The speaker is impressed by the model's ability to capture the specific 'Apple design aesthetic' with minimal prompting. This section highlights the practical utility of the model for frontend developers and designers.

Creative Coding: The Mr. Burns Campaign Site

To test creativity, the speaker provides a single image of Mr. Burns from The Simpsons and asks for a presidential campaign website. The model analyzes the character's signature traits to create a punchy, humorous site filled with 'elite-focused' policies and easter eggs. It even includes a functional Konami code trigger that changes the site's slogan to 'Excellent' when entered. The presenter praises the output as being far superior to the 'purplish slop' typically generated by other AI models. This demonstrates the model's sophisticated understanding of character context and creative web design.

Testing the Agent Swarm and Data Retrieval

The presenter moves to the official Kimi chatbot to test the Agent Swarm feature for a complex research task on AI model market shares. The UI is described as 'gamified,' showing agents with individual ID badges and real-time status updates as they browse the web and write code. While the process is visually engaging, the final PDF report is criticized for poor design choices, such as unreadable text colors. The report includes statistics like '81% of developers use AI' and mentions Claude 4.5 and Llama 4. However, the focus remains on the multi-threaded execution rather than just the final document. This section illustrates the 'playful' user experience Moonshot AI aims to provide.

Final Verdict: Reliability vs. Aesthetics

The video ends on a disappointing note as the presenter discovers the model used outdated data from 2025 instead of the requested 2026 information. This 'typical LLM behavior' leads to a loss of 10 minutes and many tokens, highlighting a significant reliability gap. Despite this, the speaker concludes that Kimi K2.5 is excellent for creating 'truly beautiful' websites that could win design awards. He compares it to Claude Code, noting that while Kimi looks better, other models might be more reliable for raw data tasks. The viewer is encouraged to explore both tools to find the right balance for their specific needs.

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