Kimi K3 Is Fable Level... (they should be worried)

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00:00:00Kimi K3 is here and honestly this one is kind of shocking. It didn't just catch up with Opus and
00:00:04GPT 5.5, it caught up with Fable and GPT 5.6. The open models are not as far behind as we first
00:00:10thought. Let's take a look. Let's start with our announcement. Kimi K3 is a 2.8 trillion
00:00:19parameter model built on Kimi Delta Retention and Attention Residuals with native vision
00:00:24capabilities and a 1 million token context window. It's the world's first open 3 trillion class model
00:00:29designed for frontier intelligence across long horizon coding, knowledge work and reasoning.
00:00:34On all of the benchmarks that they show in this blog, Kimi K3 is either trailing behind Fable
00:00:38and GPT 5.6 Soul or even beating them on some of the other areas. Like this is such a crazy jump
00:00:43that I don't think many people predicted. Obviously though this is on their own benchmark so let's take
00:00:47a look at artificial intelligence and our third party ones and I'm happy to say the results pretty
00:00:52much match up. On this benchmark we can see that around 80% of you watching this aren't subscribed
00:00:56so go ahead and click that subscribe button if you'd like to stay up to date with all things software
00:01:00development and AI. On to the real benchmarks though starting out with the coding index it scores a 76.2 on
00:01:06this that is 0.3 points behind Fable 5 and is slightly more than GPT 5.5 more than Opus 4.8 and
00:01:12more than GPT 5.6 Luna and it only slightly loses to GPT 5.6 Soul and Terra. Like look at this leap they
00:01:19have made from their last model. If we then take a look at the agentic index it's the same story.
00:01:23It's third here losing only to Fable and Soul but that is seriously still impressive and you're used
00:01:29to this by now but it's the exact same on the intelligence index as well. So even the third
00:01:32party benchmarks confirm that this model is awesome. Sadly we don't yet have the deep SWE results as of
00:01:38recording this but if we take a look at our own benchmarks you can see that it came third again.
00:01:42Like this model just seems too good to be true. The only downsides that I can find with this model is
00:01:46that it is a little bit expensive. Unless you have a supercomputer in your house I don't think you're
00:01:50going to be running this one locally so if you go through the API it's actually priced at $3 for a
00:01:54million input tokens and $15 for a million output tokens. This is quite a big step up from Kimi K 2.6
00:02:00and it's around the same price as Sonic 5 when that discount goes away but it is cheaper than Fable 5,
00:02:06Opus and GPT 5.6. API pricing also isn't everything so if we take a look at it in practice with the cost
00:02:12per task here it's actually similar to GPT 5.6 Soul and it's about half the price of Opus 4.8 and of
00:02:17course it's cheaper than Fable and Sonic 5. So it is competitive with those Frontier closed models but
00:02:22for those of you that love open models because they're a little bit cheaper this model probably
00:02:26won't be for you. GLM 5.2 is the second best option here and it's half the price. It's also not the
00:02:31fastest model ever but to me it seems fairly competitive for this level of intelligence.
00:02:36Overall it's honestly pretty hard to have anything negative to say about this model so let's just jump
00:02:40in and see some of my local testing. The first test that I put these models through was creating me a
00:02:44complete Formula 1 racing game in 3.js that's just all in one index.html and this one is Kimi K3 going
00:02:50through Open Router. I also tested it in Kimi Code that CLI just to see if the harness does change
00:02:56anything. You can see down here that it thought for 14 minutes before it started and overall it took it
00:03:0035 minutes to make this 3.js web app and it took $1.24 in API tokens. And the results I got back are
00:03:06pretty impressive. Obviously this has no access to any external assets so it's doing its best at creating
00:03:11these models. But the track does work. We have our AI racers and they seem to be able to go around the
00:03:16track. You can see the barriers actually work so I can't clip through them. Our position is updating.
00:03:21We have our map updating. We have our current time updating as well as the laps as well. I have done
00:03:25a full lap and confirm that that all works. So it's a pretty good result for what Kimi K3 gave us.
00:03:30As I said I also tested out the different harnesses. So this is Kimi K3 but in Kimi Code. And this one
00:03:35I would say looks a little bit nicer. It's done a better job with the assets although that is just a
00:03:39style guide. There's a bit of lag there with those models but the handling is a little bit better.
00:03:43The controls are still inverted and actually seems to be a pattern in a lot of these 3.js applications
00:03:48for some reason. But again all of this handles really well and it has features like going off
00:03:52track is going to slow me down. And yeah it's done a pretty impressive job as well. But now let's
00:03:57compare this to the Frontier models. We have Fable 5 here in Claude Code that was on max and it took
00:04:0144 minutes to make my 3.js application. Then we also have GPT 5.6 Sol on max as well. And this
00:04:07one took 18 minutes. This is the result that Fable gave me. So we have Fable GP here. And I would say
00:04:12that it looks slightly nicer maybe. But again all of this is just a stylistic choice. And the controls
00:04:17aren't actually inverted in this one. There's also a bit of camera wobble which I do think is a nice
00:04:22style. And again everything seems to be working in this one like all of the others. I've tested doing
00:04:26a full lap of this as hard as it is. We do also have some collisions here as you can see. But yeah
00:04:31everything seems to be working and it's pretty comparable to what Kimi K3 gave us. It's a similar story
00:04:35with GPT 5.6 Sol. As you can see we have a working game here. Although I will note that the road here
00:04:40is grass. It didn't actually render that in. And everything does seem to be working. The controls
00:04:44are inverted on this one as well. And we also have a few backward assets. I don't know why these models
00:04:48seem to like doing that. The only one that didn't was Fable. And also the track here does get a bit
00:04:53jumbled up. So this is actually the only one that didn't make me a working track. To add in one final
00:04:57comparison. I also checked what GLM 5.2 would give me as it's the next best open model. And this one
00:05:02thought for 5 minutes and 58 seconds. Although it didn't finish it in one prompt. There was actually
00:05:07a few bugs. So I had to go back with another prompt. Even then when I did finally get the game running
00:05:11you can see that there's a lot of bugs in this one. Firstly we don't start the right way on the track.
00:05:15And there isn't really a track to begin with. And also it just looks a lot worse than the other ones.
00:05:20So there is a bit of a step up when we go up to Kimi K3. Moving on to test 2 though. I asked for a
00:05:25personal finance management dashboard. This is going to build the full stack application with a front
00:05:29end and a back end. The only thing I said I didn't want is auth. And I also asked it to seed some data.
00:05:33I did this one again in open router with K3. And then also in Kimi code. So this one is in open
00:05:38router. And you can see in total this one took 56 minutes to make me the application. And also cost
00:05:43me $1.30. This is the result they gave me though. And honestly I can't really complain about this.
00:05:48This is exactly what I asked for. It is a personal finance management dashboard. I'd say it looks
00:05:53really nice as well. And we have all of the features like the extra pages here. And I have
00:05:57checked the adding funds and sending money. It all works. So it's done a very good job. Now I'm also
00:06:01always curious to see what tools it used to do the task. Because I don't actually give it any
00:06:05instructions on what stack to use in the prompt. You can see for the front end here it went with
00:06:09react and react dom. It didn't actually use any router or anything like that. It actually built its
00:06:12own view system. So I probably would have preferred that you use something like react router,
00:06:16tan stack or next.js. And then on the back end it also built out its own server. I believe this
00:06:21one is using express.js as we can see down here. But then it also built its database just using a
00:06:26JSON file. Didn't use any SQLite or anything like that or drizzle which I probably would have liked to
00:06:31see if we were to scale this app in the future. But again obviously me knowing that I could have
00:06:35given that in the prompt. But I always like to see what these will pick as their default. This is a
00:06:38result I actually got using K3 via Kimi code. And you can see this one is actually a bit simpler.
00:06:43It's only one page and it doesn't have our sidebar. Again all of the features are working and it has
00:06:47a pretty similar look to what we got out of open router. Looking at the code though I
00:06:51do actually prefer what Kimi code gave us here with K3. It's got a pretty similar front end where it
00:06:55just uses react and no routing library. But the server did actually use a database. You can see
00:06:59it's built and expressed here. We do actually have a finance database and it's actually using node
00:07:04SQLite. Now if you compare this to the frontier models again this one is Fable 5 in Claude code.
00:07:08You can see it worked for 56 minutes on that max effort. And then I also have GPT 5.6 soul max
00:07:13where it thought for 31 minutes to make the application. Here's what Fable 5 gave us and
00:07:17honestly it's a pretty similar design. I mean there's not much more you can actually do with a
00:07:21personal finance dashboard. And all of the features do work in here. It's actually gone with a bit of a
00:07:25different style for the fonts which I've seen Fable and Opus do quite a lot lately. They seem to be
00:07:29retraining it to move away from some of those previous AI looks that they had and they're building in a new
00:07:34AI look. And this seems to be the one they're picking. I'd say these charts are actually a little
00:07:38more useless than what we got out of Kimi K3. But overall it looks pretty similar and it works
00:07:43basically the same. Even the code is pretty similar. You can see it chose React for the front
00:07:47end and it didn't actually use a router either. It wrote its own. And then also in the database it
00:07:51did successfully use a database properly. So we're using Node SQL in this one as well. And for the
00:07:57actual server it's just running Express 2. Moving on to GPT 5.6 soul though. This one is a bit of a
00:08:02weird one. It's definitely my favorite design out of the lot. And again all of the features are
00:08:06working. Let me know if you agree that this is the best design. But the weird part is in the code.
00:08:11This is definitely the most complete application code that we have seen in these examples. It
00:08:15actually built out a full NextJS application and it used Drizzle just as I would. And it used NextJS
00:08:20as well for the front end as well as the server. But the part I find a little bit weird is that it
00:08:24chose to host it on Cloudflare which isn't odd by itself but it also used for Next. And it's not
00:08:29necessarily that I wouldn't recommend that. I just think it's a little bit untested. And it's pretty
00:08:33new which shows that they're actually pushing GPT 5.6 soul to use this. And I can only speculate as to
00:08:38why but it seems it might be because that's how that ChatGPT sites actually work. You can
00:08:42see here actually decided to host this for me on that ChatGPT site feature even though I didn't ask
00:08:47it to. Personally I don't really like that very much when I'm coding an application. I don't want
00:08:50it to host it for me. I'd prefer to handle all of that myself. But I could have asked that in the
00:08:54prompt. I kind of would prefer that I have to ask it to host it instead of the other way around.
00:08:58The final result I have here is GLM 5.2 and this one's done a pretty similar thing to what Kimi K3
00:09:04did in Kimi Code where it's just built this single page. But again all of the features work and I do
00:09:08think this design is pretty nice. GLM 5.2 actually took 15 minutes to do this and you can see it cost
00:09:13me a dollar and 11 cents. As for the actual code GLM 5.2 chose to go down the Next.js route as well
00:09:19which I do actually like. But it did build out its own store instead of using a database. So all of this
00:09:24it's just in memory in JavaScript. So from my quick test there I think Kimi K3 does stand up with Fable
00:09:29and GPT 5.6 Sol and live up to the hype that the benchmarks are giving it. And honestly it's getting
00:09:33quite hard to show you just how powerful these models are in a video demonstration. You tend to
00:09:38have to use them over a course of a week in a production code base to actually see the quality
00:09:42of the code. If you have any ideas for tests that I can actually show off in a video that would
00:09:46actually put these models through a hard test let me know in the comments down below. I do also want
00:09:50to show off some of the examples that they had in their tech blog. You can see Kimi
00:09:53K3 built this game here but did have another tool to actually generate these assets so the cowboy and
00:09:58the horse weren't generated by K3. They were gone elsewhere. You can see he's done a very good job
00:10:03of this in 3GS. And the other thing that's crazy is this chip design one. You can see as an early
00:10:08proof of concept Kimi K3 designed a chip to serve a nano model built on its own architecture. In a single
00:10:1348 hour autonomous run K3 built, optimized and verified the chip using open source tools. So hopefully
00:10:19you've seen that this model is absolutely awesome and it's definitely going to be a bit of a hit to
00:10:23these frontier closed labs. Or at least it will be when they actually drop the weights. They haven't
00:10:27dropped them yet but they do plan on doing so. So I hope we see them very soon. What do you think
00:10:32about this? Did you expect a Chinese lab to catch up this quickly? And does this model appeal to you?
00:10:36Let me know in the comments down below. While you're there, subscribe. And as always, see you in the next one.

Key Takeaway

Kimi K3 is a high-performance open 3 trillion class model that matches the coding and reasoning capabilities of frontier models like Fable 5 and GPT 5.6 at a more competitive price point.

Highlights

  • Kimi K3 is a 2.8 trillion parameter model featuring native vision capabilities and a 1 million token context window.

  • The model achieves a 76.2 coding index score, placing it within 0.3 points of Fable 5.

  • API pricing for Kimi K3 is set at $3 per million input tokens and $15 per million output tokens.

  • In a 48-hour autonomous run, Kimi K3 successfully designed, optimized, and verified a chip for a nano model using open-source tools.

  • Kimi K3 performs competitively with frontier models like Fable 5 and GPT 5.6 across coding, agentic, and intelligence benchmarks.

Timeline

Kimi K3 Architecture and Benchmarks

  • Kimi K3 is built on Kimi Delta Retention and Attention Residuals.
  • The model is designed for frontier-level intelligence in coding, knowledge work, and reasoning.
  • Third-party benchmarks confirm that Kimi K3 trails only Fable and GPT 5.6 models in coding and agentic tasks.

Kimi K3 represents a significant leap in open model capabilities as a 2.8 trillion parameter model. It features native vision support and a 1 million token context window, allowing it to perform at a level comparable to top-tier closed models. Testing results across coding and agentic indexes validate its position as a top-three competitor in the current AI landscape.

API Pricing and Comparative Costs

  • API access costs $3 per million input tokens and $15 per million output tokens.
  • Kimi K3 is priced similarly to Sonic 5 but remains cheaper than Fable 5, Opus 4.8, and GPT 5.6.
  • The model provides a cost-effective alternative for high-level intelligence compared to current frontier closed models.

While the model is more expensive than its predecessor Kimi K 2.6, its pricing structure remains competitive with industry-leading frontier models. It serves as a viable option for those requiring advanced intelligence at a lower cost than Fable 5 or Opus. However, it is not positioned as a low-cost budget model, with GLM 5.2 remaining the cheaper alternative for those specific needs.

Practical Testing: Racing Game and Finance Dashboard

  • Kimi K3 successfully generated a functional 3.js Formula 1 racing game in 35 minutes.
  • The model built a full-stack personal finance dashboard using React and Express.js with SQLite integration.
  • Performance in coding tasks shows high consistency and functionality when compared to Fable 5 and GPT 5.6.

Practical application tests confirm the model's ability to handle complex coding tasks. In game development, the model produced functional mechanics and collision detection. For web application development, it demonstrated the ability to select appropriate stacks, including databases like SQLite, often matching the structural quality produced by frontier closed models.

Autonomous Chip Design and Future Outlook

  • Kimi K3 autonomously designed and verified a chip architecture over a 48-hour period.
  • The creators plan to release model weights in the future.
  • The release challenges the current dominance of frontier closed labs.

Beyond software, the model demonstrates high-level reasoning through autonomous hardware design proofs. The ability to utilize open-source tools to complete complex, multi-day engineering tasks underscores its utility. The pending release of model weights is expected to shift the competitive landscape for open-source AI development.

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