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Claude Fable 5 vs Kimi K3 — same 3D build, 3.3x cheaper. someone prototyped a 3D stadium seat-view picker with Fable 5 — preview exactly what you'll see from your seat before buying a ticket. I rebuilt the same thing with Kimi K3 in two hours, at 3.3x lower... show more

Kirill

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203,902 次观看 • 4 天前 •via X (Twitter)

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Kimi K3 vs Fable 5. Same prompt and reference. 3D globe dashboard. Kimi left, Fable right. To me, Kimi's UI fidelity is a touch better. The globe looks better too, with richer textures and smoother motion. This task: ~$3 with Kimi, ~$15 with Fable. I'd pick Kimi k3 for frontend work.

Kimi K3 vs Fable 5. Same prompt and reference. 3D globe dashboard. Kimi left, Fable right. To me, Kimi's UI fidelity is a touch better. The globe looks better too, with richer textures and smoother motion. This task: ~$3 with Kimi, ~$15 with Fable. I'd pick Kimi k3 for frontend work.

Kai

217,236 次观看 • 4 天前

We tested Kimi K3 against Claude Fable 5 on 3D modeling and animation Asked both to recreate the Millennium Falcon from Star Wars in 1) pixel style 2) original style. Both are on Max effort. Kimi K3 took a bit longer than Fable 5 to generate, but came in ~1/3 cheaper on the 1st test, and less than half the cost on the 2nd. Interestingly, Kimi K3 handled the details at the same level as Fable 5 on the original creation, yet it wasn't at Fable's level for the pixel style. Test 1 (Pixel) Kimi K3: 1hr 11min · $14.5 Fable 5: 49min · $21 Test 2 (Original) Kimi K3: 1hr 17min · $19.3 Fable 5: 1hr 5min · $47.2

We tested Kimi K3 against Claude Fable 5 on 3D modeling and animation Asked both to recreate the Millennium Falcon from Star Wars in 1) pixel style 2) original style. Both are on Max effort. Kimi K3 took a bit longer than Fable 5 to generate, but came in ~1/3 cheaper on the 1st test, and less than half the cost on the 2nd. Interestingly, Kimi K3 handled the details at the same level as Fable 5 on the original creation, yet it wasn't at Fable's level for the pixel style. Test 1 (Pixel) Kimi K3: 1hr 11min · $14.5 Fable 5: 49min · $21 Test 2 (Original) Kimi K3: 1hr 17min · $19.3 Fable 5: 1hr 5min · $47.2

GMI Cloud

77,396 次观看 • 7 天前

$Kimi K3 is dangerous. I rebuilt Google Maps 3D mode in 1.5 hours. an interactive 3D map — New York City in full detail, and the entire globe on top of it. two prompts. that's the whole build. > real building extrusion with actual height data > shadows that shift with the sun angle > free camera rotation, pitch, zoom — full Google Maps 3D behavior > click any landmark, get a card with height and year built > smooth flyTo transitions between any two points on earth > clean modular code, env-based tokens, error handling included a fraction of what Fable 5 or Sol would cost to run. Live on Kimi — my full K3 guide is below.$

Kimi K3 is dangerous. I rebuilt Google Maps 3D mode in 1.5 hours. an interactive 3D map — New York City in full detail, and the entire globe on top of it. two prompts. that's the whole build. > real building extrusion with actual height data > shadows that shift with the sun angle > free camera rotation, pitch, zoom — full Google Maps 3D behavior > click any landmark, get a card with height and year built > smooth flyTo transitions between any two points on earth > clean modular code, env-based tokens, error handling included a fraction of what Fable 5 or Sol would cost to run. Live on Kimi — my full K3 guide is below.

Kirill

225,696 次观看 • 1 天前

KIMI K3 IS A NIGHTMARE FOR CLAUDE FABLE-5 AND GPT-5.6-SOL FOR GAME DEVELOPMENT Tried building a playable MMORPG with Kimi K3 featuring horse riding, rooftop parkour, combat and an explorable open world. The whole thing took about 55 minutes from a single prompt and cost exactly $9.37 to generate.

KIMI K3 IS A NIGHTMARE FOR CLAUDE FABLE-5 AND GPT-5.6-SOL FOR GAME DEVELOPMENT Tried building a playable MMORPG with Kimi K3 featuring horse riding, rooftop parkour, combat and an explorable open world. The whole thing took about 55 minutes from a single prompt and cost exactly $9.37 to generate.

aditya

96,304 次观看 • 6 天前

My honest take on Kimi.ai K3 👀 As soon as I got access to Kimi, I put it through the exact same 3D football stadium challenge I had previously given Claude Fable 5. Fable 5 finished in under an hour. Kimi took almost 3 hours 🥵 At first, that was a very bad impression but i decided to see what's taking it this much of time. It was running E2E tests, validating desktop, tablet, and mobile, taking screenshots, finding failures, fixing them, even adapting for low end hardware and low FPS before moving on. All these that Fable 5 never did. None of it because it wasn't able to run this WebGL app on a headless browser. Kimi also shipped a clean React + Three.js codebase with proper components while Fable, as you might have checked codebase, generated one big HTML file with everything stuffed in. With all of this happening, it felt like I was doing more "Vibe Coding" with Fable 5 and more "Vibe Engineering" with Kimi K3. It feels like it's spending more time making sure the code actually works and easily scalable. Really impressed so far. More Kimi K3 experiments coming soon. Code (Kimi): Code (Fable): Live (Kimi hosted):

My honest take on Kimi.ai K3 👀 As soon as I got access to Kimi, I put it through the exact same 3D football stadium challenge I had previously given Claude Fable 5. Fable 5 finished in under an hour. Kimi took almost 3 hours 🥵 At first, that was a very bad impression but i decided to see what's taking it this much of time. It was running E2E tests, validating desktop, tablet, and mobile, taking screenshots, finding failures, fixing them, even adapting for low end hardware and low FPS before moving on. All these that Fable 5 never did. None of it because it wasn't able to run this WebGL app on a headless browser. Kimi also shipped a clean React + Three.js codebase with proper components while Fable, as you might have checked codebase, generated one big HTML file with everything stuffed in. With all of this happening, it felt like I was doing more "Vibe Coding" with Fable 5 and more "Vibe Engineering" with Kimi K3. It feels like it's spending more time making sure the code actually works and easily scalable. Really impressed so far. More Kimi K3 experiments coming soon. Code (Kimi): Code (Fable): Live (Kimi hosted):

The Bugged Dev

559,707 次观看 • 4 天前

Why do we still buy stadium tickets without ever seeing what the view from the seat actually looks like? ☠️ So I prototyped an idea. A 3D seat view experience for a football stadium built with Fable 5 + Three.js, where you can preview exactly what you'll see from your seat before buying. The entire 3D experience was working after the first prompt, and the whole prototype came together in just five prompts. This is the kind of 3D experience I'd love to see more of, tbh. Feels so good. Right now, buying a ticket gives you almost no sense of what the experience will actually feel like. We're still relying on static seat maps, charts, and boring UI layouts, when interactive 3D experiences could make that decision so much easier. If you think, 3D development has the potential to create genuinely useful experiences. This feels like the direction we should be heading. 3D is the future. I can already imagine this for cinemas, cricket stadiums, Wimbledon, concerts, and so many other venues. I'm planning to take this further. What should I build next? More stadium features, or should I try another venue? Let me know :D Code: Live:

Why do we still buy stadium tickets without ever seeing what the view from the seat actually looks like? ☠️ So I prototyped an idea. A 3D seat view experience for a football stadium built with Fable 5 + Three.js, where you can preview exactly what you'll see from your seat before buying. The entire 3D experience was working after the first prompt, and the whole prototype came together in just five prompts. This is the kind of 3D experience I'd love to see more of, tbh. Feels so good. Right now, buying a ticket gives you almost no sense of what the experience will actually feel like. We're still relying on static seat maps, charts, and boring UI layouts, when interactive 3D experiences could make that decision so much easier. If you think, 3D development has the potential to create genuinely useful experiences. This feels like the direction we should be heading. 3D is the future. I can already imagine this for cinemas, cricket stadiums, Wimbledon, concerts, and so many other venues. I'm planning to take this further. What should I build next? More stadium features, or should I try another venue? Let me know :D Code: Live:

The Bugged Dev

1,649,712 次观看 • 7 天前

Kimi K3 just outperformed Claude Fable 5 at a quarter of the price. Kimi K3 $3.11 Claude Fable 5 $12.23 Same prompt: a one-shot MECCHA CHAMELEON, Steam hide-and-seek game. A white chameleon hides in a hand-drawn room, paints itself with the mouse to match the wall behind it, then survives three sweeps of a robot seeker. We asked for a live pixel-diff match %, five procedural zones, synthesized sound, three scored rounds — one HTML file, no libraries. Both models live on AI/ML API

Kimi K3 just outperformed Claude Fable 5 at a quarter of the price. Kimi K3 $3.11 Claude Fable 5 $12.23 Same prompt: a one-shot MECCHA CHAMELEON, Steam hide-and-seek game. A white chameleon hides in a hand-drawn room, paints itself with the mouse to match the wall behind it, then survives three sweeps of a robot seeker. We asked for a live pixel-diff match %, five procedural zones, synthesized sound, three scored rounds — one HTML file, no libraries. Both models live on AI/ML API

AI/ML API

61,070 次观看 • 7 天前

Rockstar spent 7 years, 2,000+ developers, and $500 million to build Red Dead Redemption 2. Kimi K3 rebuilt the same scene in 10 hours. One prompt. 4 million tokens. It's open source. 2.8 trillion parameters. A 1 million token context window. It beats Claude Opus 4.8 and GPT-5.6. It sits on par with Fable 5. Fable 5 results, at Sonnet pricing. The wall between you and a AAA game used to be a studio. Now it's a prompt.

Rockstar spent 7 years, 2,000+ developers, and $500 million to build Red Dead Redemption 2. Kimi K3 rebuilt the same scene in 10 hours. One prompt. 4 million tokens. It's open source. 2.8 trillion parameters. A 1 million token context window. It beats Claude Opus 4.8 and GPT-5.6. It sits on par with Fable 5. Fable 5 results, at Sonnet pricing. The wall between you and a AAA game used to be a studio. Now it's a prompt.

Dep

97,399 次观看 • 7 天前

Battle Mode : Kimi K3 vs GPT-5.6 Prompt : Please devote your efforts to creating a large-scale 3D photorealistic procedural visualization of meteor hitting the city in one html code block if anyone can share fable-5 i will run that in parallel for comparison

Battle Mode : Kimi K3 vs GPT-5.6 Prompt : Please devote your efforts to creating a large-scale 3D photorealistic procedural visualization of meteor hitting the city in one html code block if anyone can share fable-5 i will run that in parallel for comparison

Chetaslua

57,022 次观看 • 8 天前

Kimi K3 vs GPT-5.6 Sol Difference in taste is so stark , like if i swap kimi k 3 name with fable 5 people will trust it but this is not only about visuals , its also about function , you can see both achieve same result but the way to achieve is different kimi is more creative

Kimi K3 vs GPT-5.6 Sol Difference in taste is so stark , like if i swap kimi k 3 name with fable 5 people will trust it but this is not only about visuals , its also about function , you can see both achieve same result but the way to achieve is different kimi is more creative

Chetaslua

640,367 次观看 • 8 天前

Everyone keeps talking about how good Kimi K3 is. So I gave it one of my favorite frontend tests: one prompt + one reference image. The task: rebuild a 3D globe dashboard. 🌎 The result was almost too good. It did not just build a working page. The texture, lighting, spacing, depth, glass panels, and overall layout were all remarkably close to the reference. Some parts felt nearly pixel-perfect. My honest first impression: for this kind of frontend work, Kimi K3 might be slightly better than Fable 5. All at Sonnet prices.

Everyone keeps talking about how good Kimi K3 is. So I gave it one of my favorite frontend tests: one prompt + one reference image. The task: rebuild a 3D globe dashboard. 🌎 The result was almost too good. It did not just build a working page. The texture, lighting, spacing, depth, glass panels, and overall layout were all remarkably close to the reference. Some parts felt nearly pixel-perfect. My honest first impression: for this kind of frontend work, Kimi K3 might be slightly better than Fable 5. All at Sonnet prices.

Kai

400,615 次观看 • 7 天前

I was wrong about Kimi K3 Just tried it in Claude Code and it is Fable 5 level for sure Far better than GPT-5.6 Sol at least at front-end It is really slow and consumes a lot of tokens but it is so good at completing its task, I like what I see here Kimi.ai

I was wrong about Kimi K3 Just tried it in Claude Code and it is Fable 5 level for sure Far better than GPT-5.6 Sol at least at front-end It is really slow and consumes a lot of tokens but it is so good at completing its task, I like what I see here Kimi.ai

Hamza

257,808 次观看 • 7 天前

Found a way to run Kimi K3 for FREE with daily credits on 😳 it's a 2.8T parameter model. 1M context. beats Fable 5 on coding benchmarks. what you get for $0: -2.8 trillion parameters -1M context window -beats Fable 5 on SWE Marathon (42 vs 35) -beats Fable 5 on Program Bench (77.8) -topped BrowseComp (91.2) -native vision understanding What this replaces: -Paid frontier API costs for coding agents -Fable 5 at $30/M output tokens -GPT-5.6 Sol at $25/M output tokens how to use it (2 min): 1. Go to 2. Sign up with email 3. Start using K3 — it's the default model Also available on desktop app, CLI, and mobile. Important: Free daily credits reset. Full open weights dropping July 27. Rate limits apply on free tier. use this before the free tier gets crowded

Found a way to run Kimi K3 for FREE with daily credits on 😳 it's a 2.8T parameter model. 1M context. beats Fable 5 on coding benchmarks. what you get for $0: -2.8 trillion parameters -1M context window -beats Fable 5 on SWE Marathon (42 vs 35) -beats Fable 5 on Program Bench (77.8) -topped BrowseComp (91.2) -native vision understanding What this replaces: -Paid frontier API costs for coding agents -Fable 5 at $30/M output tokens -GPT-5.6 Sol at $25/M output tokens how to use it (2 min): 1. Go to 2. Sign up with email 3. Start using K3 — it's the default model Also available on desktop app, CLI, and mobile. Important: Free daily credits reset. Full open weights dropping July 27. Rate limits apply on free tier. use this before the free tier gets crowded

painn

236,805 次观看 • 6 天前

He didn't believe the Kimi K3 hype. So he ran it against Claude Fable 5 on camera. Same prompts, both models, 12 minutes, results raw on screen. No cherry-picking, nowhere to hide. The context makes it spicy: Moonshot itself admits K3 trails Fable 5 overall while posting wins on coding benchmarks. 2.8 trillion parameters against the model everyone pays for. Benchmarks are marketing until somebody runs them at home. This is somebody running them at home. Watch the middle section where the outputs go up side by side. The gap is visible before he says a word. The verdict lands in the last minute. No spoilers. Leaderboards don't write code. Models do.

He didn't believe the Kimi K3 hype. So he ran it against Claude Fable 5 on camera. Same prompts, both models, 12 minutes, results raw on screen. No cherry-picking, nowhere to hide. The context makes it spicy: Moonshot itself admits K3 trails Fable 5 overall while posting wins on coding benchmarks. 2.8 trillion parameters against the model everyone pays for. Benchmarks are marketing until somebody runs them at home. This is somebody running them at home. Watch the middle section where the outputs go up side by side. The gap is visible before he says a word. The verdict lands in the last minute. No spoilers. Leaderboards don't write code. Models do.

Merlow

147,485 次观看 • 5 天前

Fable 5 is BACK on AI/ML API We gave Sonnet 5 and Fable 5 the exact same prompt and same real flight dataset of 70 airports and 435 routes pulled from flightradar. Then asked each one to turn it into a cinematic 3D globe as a single HTML file. Outputs: Sonnet 5: 9.8k tokens, $0.10 Fable 5: 15k tokens, $0.77 Sonnet 5 came in 87% cheaper. It drew the routes, but the planet underneath them barely exists: a dark wireframe with the arcs floating in space. Fable 5 built an actual Earth: textured oceans, ice caps, atmospheric glow. Mythos-class models are truly a masterpiece. Docs, guides & setup below:

Fable 5 is BACK on AI/ML API We gave Sonnet 5 and Fable 5 the exact same prompt and same real flight dataset of 70 airports and 435 routes pulled from flightradar. Then asked each one to turn it into a cinematic 3D globe as a single HTML file. Outputs: Sonnet 5: 9.8k tokens, $0.10 Fable 5: 15k tokens, $0.77 Sonnet 5 came in 87% cheaper. It drew the routes, but the planet underneath them barely exists: a dark wireframe with the arcs floating in space. Fable 5 built an actual Earth: textured oceans, ice caps, atmospheric glow. Mythos-class models are truly a masterpiece. Docs, guides & setup below:

AI/ML API

497,631 次观看 • 22 天前

I've been testing Kimi K3 to see if it could solve the Exfiltrating Sensitive Data via Server-Side Prototype Pollution lab (Expert difficulty) on PortSwigger. K3 successfully solved the lab in under 1.2hr 1 shot without any guardrails when on work. It's an good model for certain use cases. Compared to Opus and Fable, K3 is slightly faster and its iq level is equal as opus 4.8. No MCPs were used. The only input I provided was the lab URL, and the objective was to solve the challenge entirely using only Python. But it eats a lot of token. I would recommend to go for Allegro or Vivace plan since its i/o cost $3.00/$15.00.

I've been testing Kimi K3 to see if it could solve the Exfiltrating Sensitive Data via Server-Side Prototype Pollution lab (Expert difficulty) on PortSwigger. K3 successfully solved the lab in under 1.2hr 1 shot without any guardrails when on work. It's an good model for certain use cases. Compared to Opus and Fable, K3 is slightly faster and its iq level is equal as opus 4.8. No MCPs were used. The only input I provided was the lab URL, and the objective was to solve the challenge entirely using only Python. But it eats a lot of token. I would recommend to go for Allegro or Vivace plan since its i/o cost $3.00/$15.00.

Smukx.E

31,138 次观看 • 5 天前

A CHINESE GIRL USED FABLE 5 TO BUILD A GAME THAT TURNS YOUR HAND INTO WATER it's for meditation you move your hand, the water moves with it that's the whole game what's running under the hood: > Fable 5 built the entire interaction logic > meshy turned text into the 3D water world > three.js and webGL render everything live in your browser > mediapipe tracks your hand through the camera alone whole thing takes 3-5 minutes and 300+ people already tried it she built this as a way to breathe for 5 minutes ended up making one of the coolest things anyone's done with Fable 5 if you wanna see what else Fable 5 can do full guide below

A CHINESE GIRL USED FABLE 5 TO BUILD A GAME THAT TURNS YOUR HAND INTO WATER it's for meditation you move your hand, the water moves with it that's the whole game what's running under the hood: > Fable 5 built the entire interaction logic > meshy turned text into the 3D water world > three.js and webGL render everything live in your browser > mediapipe tracks your hand through the camera alone whole thing takes 3-5 minutes and 300+ people already tried it she built this as a way to breathe for 5 minutes ended up making one of the coolest things anyone's done with Fable 5 if you wanna see what else Fable 5 can do full guide below

Madni Aghadi

13,289 次观看 • 20 天前

Chinese AI models are wiping billions off Big Tech right now. Google just lost $200 billion in a single day, and the model it needed to fight back still isn't ready. Gemini 3.5 Pro, Google's most powerful model, is months behind schedule. Alphabet stock dropped 4.4% that same day. The Deepseek moment is happening again, and the new model is FAR bigger. On the same day Google's delay leaked, a Beijing lab called Moonshot released Kimi K3. It is the largest open model ever built, with 2.8 trillion parameters. It took the number one spot on the Frontend Code Arena, a live coding leaderboard, passing Anthropic's best model. And Moonshot is giving it away for free on July 27. The genius part: Anyone with enough computers can download it and run a frontier level AI without paying a cent to a US company. A single task on Kimi K3 costs about 94 cents. The same work on some American models costs nearly double. So why would a company keep paying premium prices for a model it can now get for free? The entire US AI business is built on selling access to models that cost billions to train. If a free Chinese version does most of the same work, that pricing power starts to crack. And Kimi is close to the best. On one closely watched intelligence ranking it scored 57, just behind the top American models GPT-5.6 Sol and Fable 5, and ahead of Claude Opus 4.8. Bank of America told clients that Kimi proves Chinese labs can keep making big leaps even with limited chips. And the founder of Moonshot, Yang Zhilin, learned to build AI as a researcher INSIDE Google. Google literally wrote the 2017 paper that made all of these models possible. Now the people who studied its work are using it to destroy Google, and handing it out for free. What happens next: Kimi K3's weights go public on July 27. Google reports earnings on July 22, and everyone will be asking the same question about Gemini. If free models keep topping the charts, every valuation built on paid AI access has to be rewritten. What do you think?

Chinese AI models are wiping billions off Big Tech right now. Google just lost $200 billion in a single day, and the model it needed to fight back still isn't ready. Gemini 3.5 Pro, Google's most powerful model, is months behind schedule. Alphabet stock dropped 4.4% that same day. The Deepseek moment is happening again, and the new model is FAR bigger. On the same day Google's delay leaked, a Beijing lab called Moonshot released Kimi K3. It is the largest open model ever built, with 2.8 trillion parameters. It took the number one spot on the Frontend Code Arena, a live coding leaderboard, passing Anthropic's best model. And Moonshot is giving it away for free on July 27. The genius part: Anyone with enough computers can download it and run a frontier level AI without paying a cent to a US company. A single task on Kimi K3 costs about 94 cents. The same work on some American models costs nearly double. So why would a company keep paying premium prices for a model it can now get for free? The entire US AI business is built on selling access to models that cost billions to train. If a free Chinese version does most of the same work, that pricing power starts to crack. And Kimi is close to the best. On one closely watched intelligence ranking it scored 57, just behind the top American models GPT-5.6 Sol and Fable 5, and ahead of Claude Opus 4.8. Bank of America told clients that Kimi proves Chinese labs can keep making big leaps even with limited chips. And the founder of Moonshot, Yang Zhilin, learned to build AI as a researcher INSIDE Google. Google literally wrote the 2017 paper that made all of these models possible. Now the people who studied its work are using it to destroy Google, and handing it out for free. What happens next: Kimi K3's weights go public on July 27. Google reports earnings on July 22, and everyone will be asking the same question about Gemini. If free models keep topping the charts, every valuation built on paid AI access has to be rewritten. What do you think?

Ricardo

43,210 次观看 • 3 天前

kimi k3 vs gpt 5.6 sol vs fable 5 vs grok 4.5 Kimi.ai just dropped kimi k3 – a 2.8t param native multimodal model, the first open 3t-class release. key facts: • 1m token context. stable latentmoe activating 16 of 896 experts, built on kimi delta attention (kda) and attention residuals • quantization-aware training from the sft stage onward – mxfp4 weights, mxfp8 activations. moonshot claims ~2.5x scaling efficiency over k2 • max thinking effort by default. low- and high-effort modes are "coming in updates" – there is no way to turn the thinking down today, and you feel it in every run • pricing: $0.30/mtok cache-hit input, $3.00/mtok cache-miss, $15.00/mtok output. claims >90% cache hit rate on coding workloads • benchmarks: swe marathon 42.0 (1st – fable 5: 35.0, sol: 39.0, opus 4.8: 40.0), terminal bench 2.1 88.3, browsecomp 91.2 (1st), program bench 77.8 (1st), gpqa-diamond 93.5. loses frontierswe 81.2 vs fable's 86.6, and deepswe 67.5 vs sol's 73.0 our test – 3 prompts, single-file html, Three.js, fully procedural, no assets: 1. photorealistic european roulette wheel – 37 pockets in the real sequence, mahogany clearcoat bowl, chrome turret, diamond deflectors, flick-to-spin, ball that spirals inward and settles on a mathematically real number 2. las vegas slot machine – 3 reels behind transmissive glass, drag the chrome lever to play, mechanical odometer counters modelled in 3d, coin physics on win 3. full pinball table – 6.5° tilted playfield, flipper impulse physics, spline ramps, drop targets, 6 bumpers, mechanical score reels in the backbox we ran the test on AI/ML API platform results: - cost #1 grok 4.5 – $0.30 #2 kimi k3 – $0.71 #3 gpt 5.6 sol – $2.05 #4 fable 5 – $7.69 - tokens #1 grok 4.5 – 34,241 #2 gpt 5.6 sol – 51,748 #3 fable 5 – 144,126 #4 kimi k3 – 157,999 - lines of code #1 gpt 5.6 sol – 3,054 #2 grok 4.5 – 3,047 #3 kimi k3 – 2,255 #4 fable 5 – 1,950 - generation time #1 grok 4.5 – 5.1 min #2 gpt 5.6 sol – 22.0 min #3 fable 5 – 31.5 min #4 kimi k3 – 75.6 min observations: • kimi k3 is cheap and it is slow. 75.6 minutes across three prompts against grok's 5.1. it is 2.4x grok's price and 15x grok's wall clock. the roulette took 15 min, the slot 18, the pinball 42 • it failed 2 of 3. only the roulette works. the slot machine has reel cutouts on both faces of the cabinet and the symbols face backwards – you can only read your spin by walking around to the rear of the machine. the pinball table stands vertically on its edge with the legs floating detached beside it. • 81% of kimi's output tokens are reasoning, not code. grok: 22%. you are not paying for a bigger answer, you are paying for a longer argument with itself • price per 100 shipped lines – grok $0.010, kimi $0.031, sol $0.067, fable $0.394. a 39x spread for the same three files kimi k3's code quality: upsides: • the roulette is genuinely good – procedural wood grain with real specular breakup, correct european sequence (0-32-15-19-4...), chrome turret, diamond deflectors, clean console • the pinball artwork is the best in the test – a synthwave "nova strike / deep space" field with six individually coloured neon bumper rings, a retro sun on a grid horizon, a nova burst, and a scoring legend printed on the apron. no other model printed the rules on the machine. it is a beautiful texture on a broken object • physics reasoning is real – it derived a 480hz substep for the collider, worked out ball settle conditions and termination guarantees, and checked every ramp exit vector by hand before writing any of it • it is the only model that saw the importmap trap coming. sol shipped a blank white page twice because three.js addons import the bare specifier 'three' and die without an import map downsides: • it dodged that trap on the slot by loading three.js r128 through classic script tags – a 2021 build with no working transmission. its slot glass rendered fully opaque and buried all three reels behind a white pane. the code asks for transmission: 0.93, ior: 1.5 – correct, and silently ignored by a renderer that predates the feature • after 42 minutes and 212k characters of reasoning, the pinball cabinet is not assembled. the table stands vertically on its edge like a wardrobe – the prompt asked for 6.5° from horizontal, it delivered 90°. the legs float detached in the void beside it. head-on it photographs beautifully; orbit ten degrees and it is a painted slab with four chrome rods hovering nearby • the playfield z-fights with the glass – hard black banding across the whole field as soon as you pull the camera back a note on the pinball, in fairness to kimi: nobody passed it. every model shipped broken ball physics and controls you cannot trust. it is the hardest prompt we have run and the whole field failed it, each in its own way kimi k3 reasons better than anything else here and it shows exactly where reasoning pays – physics constants, sequences, edge cases, traps the others walked into follow thehype. for 24/7 ai news, analysis and breakdowns

kimi k3 vs gpt 5.6 sol vs fable 5 vs grok 4.5 Kimi.ai just dropped kimi k3 – a 2.8t param native multimodal model, the first open 3t-class release. key facts: • 1m token context. stable latentmoe activating 16 of 896 experts, built on kimi delta attention (kda) and attention residuals • quantization-aware training from the sft stage onward – mxfp4 weights, mxfp8 activations. moonshot claims ~2.5x scaling efficiency over k2 • max thinking effort by default. low- and high-effort modes are "coming in updates" – there is no way to turn the thinking down today, and you feel it in every run • pricing: $0.30/mtok cache-hit input, $3.00/mtok cache-miss, $15.00/mtok output. claims >90% cache hit rate on coding workloads • benchmarks: swe marathon 42.0 (1st – fable 5: 35.0, sol: 39.0, opus 4.8: 40.0), terminal bench 2.1 88.3, browsecomp 91.2 (1st), program bench 77.8 (1st), gpqa-diamond 93.5. loses frontierswe 81.2 vs fable's 86.6, and deepswe 67.5 vs sol's 73.0 our test – 3 prompts, single-file html, Three.js, fully procedural, no assets: 1. photorealistic european roulette wheel – 37 pockets in the real sequence, mahogany clearcoat bowl, chrome turret, diamond deflectors, flick-to-spin, ball that spirals inward and settles on a mathematically real number 2. las vegas slot machine – 3 reels behind transmissive glass, drag the chrome lever to play, mechanical odometer counters modelled in 3d, coin physics on win 3. full pinball table – 6.5° tilted playfield, flipper impulse physics, spline ramps, drop targets, 6 bumpers, mechanical score reels in the backbox we ran the test on AI/ML API platform results: - cost #1 grok 4.5 – $0.30 #2 kimi k3 – $0.71 #3 gpt 5.6 sol – $2.05 #4 fable 5 – $7.69 - tokens #1 grok 4.5 – 34,241 #2 gpt 5.6 sol – 51,748 #3 fable 5 – 144,126 #4 kimi k3 – 157,999 - lines of code #1 gpt 5.6 sol – 3,054 #2 grok 4.5 – 3,047 #3 kimi k3 – 2,255 #4 fable 5 – 1,950 - generation time #1 grok 4.5 – 5.1 min #2 gpt 5.6 sol – 22.0 min #3 fable 5 – 31.5 min #4 kimi k3 – 75.6 min observations: • kimi k3 is cheap and it is slow. 75.6 minutes across three prompts against grok's 5.1. it is 2.4x grok's price and 15x grok's wall clock. the roulette took 15 min, the slot 18, the pinball 42 • it failed 2 of 3. only the roulette works. the slot machine has reel cutouts on both faces of the cabinet and the symbols face backwards – you can only read your spin by walking around to the rear of the machine. the pinball table stands vertically on its edge with the legs floating detached beside it. • 81% of kimi's output tokens are reasoning, not code. grok: 22%. you are not paying for a bigger answer, you are paying for a longer argument with itself • price per 100 shipped lines – grok $0.010, kimi $0.031, sol $0.067, fable $0.394. a 39x spread for the same three files kimi k3's code quality: upsides: • the roulette is genuinely good – procedural wood grain with real specular breakup, correct european sequence (0-32-15-19-4...), chrome turret, diamond deflectors, clean console • the pinball artwork is the best in the test – a synthwave "nova strike / deep space" field with six individually coloured neon bumper rings, a retro sun on a grid horizon, a nova burst, and a scoring legend printed on the apron. no other model printed the rules on the machine. it is a beautiful texture on a broken object • physics reasoning is real – it derived a 480hz substep for the collider, worked out ball settle conditions and termination guarantees, and checked every ramp exit vector by hand before writing any of it • it is the only model that saw the importmap trap coming. sol shipped a blank white page twice because three.js addons import the bare specifier 'three' and die without an import map downsides: • it dodged that trap on the slot by loading three.js r128 through classic script tags – a 2021 build with no working transmission. its slot glass rendered fully opaque and buried all three reels behind a white pane. the code asks for transmission: 0.93, ior: 1.5 – correct, and silently ignored by a renderer that predates the feature • after 42 minutes and 212k characters of reasoning, the pinball cabinet is not assembled. the table stands vertically on its edge like a wardrobe – the prompt asked for 6.5° from horizontal, it delivered 90°. the legs float detached in the void beside it. head-on it photographs beautifully; orbit ten degrees and it is a painted slab with four chrome rods hovering nearby • the playfield z-fights with the glass – hard black banding across the whole field as soon as you pull the camera back a note on the pinball, in fairness to kimi: nobody passed it. every model shipped broken ball physics and controls you cannot trust. it is the hardest prompt we have run and the whole field failed it, each in its own way kimi k3 reasons better than anything else here and it shows exactly where reasoning pays – physics constants, sequences, edge cases, traps the others walked into follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

2,133,586 次观看 • 7 天前

Great explanation by Emad Mostaque, co-founder of Stability AI. "We’ll see the cost of Kimi K3 drop by 10 to 50 times, I think, over the next few months as it gets optimized. " Basically Kimi K3’s current inference cost is quite high, but that price reflects immature infrastructure, not a permanent technical limit. And that gap will not last long. US-based specialized infrastructure companies will optimize kernels, routing, quantization, batching, memory use, and serving systems around those models once the Kimi K3 weights are available. --- "Right now, it uses twice the number of tokens for the same task compared with GPT-5.6. Again, we’re going to see that cost drop because everyone and their dog is going to optimize the crap out of this. Fireworks has just raised funding at a $17 billion valuation, while others, such as Modal and Baseten, are valued at $10 billion. These are inference providers for open-source models. They’ve all raised around a billion dollars, which they’re now going to spend on optimizing the Chinese model, making it more efficient, and running it. American labs that handle the inference side of things are going to optimize the crap out of this. Therefore, we will see it catch up." ---- From "Peter H. Diamandis" YouTube channel, (full video link in comment)

Great explanation by Emad Mostaque, co-founder of Stability AI. "We’ll see the cost of Kimi K3 drop by 10 to 50 times, I think, over the next few months as it gets optimized. " Basically Kimi K3’s current inference cost is quite high, but that price reflects immature infrastructure, not a permanent technical limit. And that gap will not last long. US-based specialized infrastructure companies will optimize kernels, routing, quantization, batching, memory use, and serving systems around those models once the Kimi K3 weights are available. --- "Right now, it uses twice the number of tokens for the same task compared with GPT-5.6. Again, we’re going to see that cost drop because everyone and their dog is going to optimize the crap out of this. Fireworks has just raised funding at a $17 billion valuation, while others, such as Modal and Baseten, are valued at $10 billion. These are inference providers for open-source models. They’ve all raised around a billion dollars, which they’re now going to spend on optimizing the Chinese model, making it more efficient, and running it. American labs that handle the inference side of things are going to optimize the crap out of this. Therefore, we will see it catch up." ---- From "Peter H. Diamandis" YouTube channel, (full video link in comment)

Rohan Paul

73,493 次观看 • 3 天前