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SITUATION EXPLAINED: Kimi K3 just beat Fable on a major coding benchmark, at a fraction of the price. • Kimi K3 beat Fable on Frontend Code Arena • The gap between Kimi and Fable is bigger than the gap between Fable and Sol • It also smashes Opus outright,...

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132,110 views • 9 days ago •via X (Twitter)

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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
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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

78,590 views • 9 days ago

Kimi K3 beating Fable and Sol on price and quality. Command Code's internal flappy bench results are in. Really impressed with the results. For Kimi K3 we set the gameplay to hard while Fable 5 and GPT-5.6 Sol were set to easier. Cost breakdown: • Kimi K3: $0.024 •Fable 5: $0.42 •GPT-5.6 Sol: $0.15 Ranking based on DX & features: •Kimi K3: 8/10 •Fable 5: 7.5/10 • GPT-5.6 Sol: 7/10 GPT 5.6 Sol max can definitely go on longer and wins the game overall, but that's something different. Grok 4.5 beats GPT 5.6 Sol on that, lol.Mm-hmm.
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Kimi K3 beating Fable and Sol on price and quality. Command Code's internal flappy bench results are in. Really impressed with the results. For Kimi K3 we set the gameplay to hard while Fable 5 and GPT-5.6 Sol were set to easier. Cost breakdown: • Kimi K3: $0.024 •Fable 5: $0.42 •GPT-5.6 Sol: $0.15 Ranking based on DX & features: •Kimi K3: 8/10 •Fable 5: 7.5/10 • GPT-5.6 Sol: 7/10 GPT 5.6 Sol max can definitely go on longer and wins the game overall, but that's something different. Grok 4.5 beats GPT 5.6 Sol on that, lol.Mm-hmm.

Ahmad Awais

254,554 views • 9 days ago

Kivine, a new model on Arena.ai, is potentially an upcoming Kimi K3 model. I got lucky and caught a comparison between Fable 5 and Kimi K3 in the Universe simulation prompt. > Fable 5 finished faster, and most UX components were more robust and easy to use. > Kimi.ai K3 was much more complex and visually appealing. At some point, if you select a planet and set the speed to x100, it will spin you around in the 1st-person pov. It seems like they are very close 👀
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Kivine, a new model on Arena.ai, is potentially an upcoming Kimi K3 model. I got lucky and caught a comparison between Fable 5 and Kimi K3 in the Universe simulation prompt. > Fable 5 finished faster, and most UX components were more robust and easy to use. > Kimi.ai K3 was much more complex and visually appealing. At some point, if you select a planet and set the speed to x100, it will spin you around in the 1st-person pov. It seems like they are very close 👀

🚨 AI News | TestingCatalog

72,267 views • 11 days ago

Kimi K3 just 3 shotted a whole walkable voxel town with drivable cars — Voxelville, around $3.24 in API usage. The same token cost would be $10.80 with Fable 5 and $6 with GPT 5.6 Sol. Fable 5 built its own Maplewood, GPT 5.6 Sol built Willowwick, but on price/quality Kimi K3 just cooked both of them. The era of free indie game development is closer than you think!
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Kimi K3 just 3 shotted a whole walkable voxel town with drivable cars — Voxelville, around $3.24 in API usage. The same token cost would be $10.80 with Fable 5 and $6 with GPT 5.6 Sol. Fable 5 built its own Maplewood, GPT 5.6 Sol built Willowwick, but on price/quality Kimi K3 just cooked both of them. The era of free indie game development is closer than you think!

Kirill

61,616 views • 6 days ago

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 cost. no more static seat maps. pick a seat, see the actual view in 3D, then buy. works for cinemas, concerts, cricket grounds, Wimbledon — any venue. K3 dropped this week: 2.8 trillion parameters, open weights July 27. 3D is the future, and it just got a lot cheaper to build. Live Fable 5: Live Kimi K3: Code: full Kimi K3 breakdown below.
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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 cost. no more static seat maps. pick a seat, see the actual view in 3D, then buy. works for cinemas, concerts, cricket grounds, Wimbledon — any venue. K3 dropped this week: 2.8 trillion parameters, open weights July 27. 3D is the future, and it just got a lot cheaper to build. Live Fable 5: Live Kimi K3: Code: full Kimi K3 breakdown below.

Kirill

204,905 views • 6 days ago

Kimi K3 passed Fable 5 on Code Arena just 6 weeks after Fable's release, landing #1 in 6 of 7 frontend domains. We sat down with Arena CEO and co-founder Anastasios Nikolas Angelopoulos for a rapid fire conversation on what the data from real-world use tells us 👇 0:00 Biggest release of the year, or overreaction? 0:33 Kimi K3 beats Fable on Code Arena: verifying the votes 1:35 1679 points: a 17-place jump from K2.6 2:37 #1 in 6 of 7 frontend domains — but still #2 in gaming 3:15 Permanent shift or snapshot? Labs distilling Chinese models 4:23 Regulating Chinese models: the case for and against 6:30 $3 in, $15 out: open source is no longer 10% of the price 7:30 If you're Anthropic or OpenAI, what's your move? 8:09 How long before the leaderboard flips again?
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Kimi K3 passed Fable 5 on Code Arena just 6 weeks after Fable's release, landing #1 in 6 of 7 frontend domains. We sat down with Arena CEO and co-founder Anastasios Nikolas Angelopoulos for a rapid fire conversation on what the data from real-world use tells us 👇 0:00 Biggest release of the year, or overreaction? 0:33 Kimi K3 beats Fable on Code Arena: verifying the votes 1:35 1679 points: a 17-place jump from K2.6 2:37 #1 in 6 of 7 frontend domains — but still #2 in gaming 3:15 Permanent shift or snapshot? Labs distilling Chinese models 4:23 Regulating Chinese models: the case for and against 6:30 $3 in, $15 out: open source is no longer 10% of the price 7:30 If you're Anthropic or OpenAI, what's your move? 8:09 How long before the leaderboard flips again?

Arena.ai

47,714 views • 2 days ago

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.
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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 views • 9 days ago

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):
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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

571,152 views • 6 days ago

Qwen 3.8 Preview is quietly catching Kimi K3 on frontend + game design.And this is just the preview. Full 3.8 is going to be a beast. We tested Qwen 3.8 Preview against Kimi K3 on 3D modeling and animation. Ran both through the same 3 prompts. Both on Max effort. Qwen 3.8 Preview was dramatically faster across the board, 3-4x quicker on every test. Kimi K3 needed 2 hours on the final scene; Qwen wrapped it in 31 minutes. Test 1 (Engine Sim) Qwen 3.8 Preview: 25min Kimi K3: 1hr 30min Test 2 (Voxel Dino Printer) Qwen 3.8 Preview: 8min Kimi K3: 45min Test 3 (Garden Scene) Qwen 3.8 Preview: 31min Kimi K3: 2hrs
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Qwen 3.8 Preview is quietly catching Kimi K3 on frontend + game design.And this is just the preview. Full 3.8 is going to be a beast. We tested Qwen 3.8 Preview against Kimi K3 on 3D modeling and animation. Ran both through the same 3 prompts. Both on Max effort. Qwen 3.8 Preview was dramatically faster across the board, 3-4x quicker on every test. Kimi K3 needed 2 hours on the final scene; Qwen wrapped it in 31 minutes. Test 1 (Engine Sim) Qwen 3.8 Preview: 25min Kimi K3: 1hr 30min Test 2 (Voxel Dino Printer) Qwen 3.8 Preview: 8min Kimi K3: 45min Test 3 (Garden Scene) Qwen 3.8 Preview: 31min Kimi K3: 2hrs

GMI Cloud

24,254 views • 4 days ago

Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test
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Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test

Chetaslua

125,446 views • 7 days ago

🤯KIMI K3 ABSOLUTELY MOGS! BEATING Opus 4.8, GPT 5.5, and even Fable 5 in multiple benchmarks. They scored 1688 on GDPval-AA v2 🔥 This is a completely different breed of open-source models Kimi creates better games and front-end designs than Fable 5, but it's 8x cheaper! The results coming out are truly impressive! I will be testing this out further and posting multiple tests today. Stay tuned!
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🤯KIMI K3 ABSOLUTELY MOGS! BEATING Opus 4.8, GPT 5.5, and even Fable 5 in multiple benchmarks. They scored 1688 on GDPval-AA v2 🔥 This is a completely different breed of open-source models Kimi creates better games and front-end designs than Fable 5, but it's 8x cheaper! The results coming out are truly impressive! I will be testing this out further and posting multiple tests today. Stay tuned!

Mark Santos

127,267 views • 9 days ago

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
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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 views • 9 days ago

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.
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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

401,626 views • 9 days ago

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
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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

246,003 views • 8 days ago

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.
1:17

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

381,002 views • 3 days ago

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.
12:11

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

147,621 views • 7 days ago

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?
1:10

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

46,789 views • 5 days ago

Opus 5 crushed Fable 5 at 3D destruction physics for 2x cheaper! We gave four models the same task: build three self-contained HTML scenes with real physics Prompts: - A tornado that sucks in a whole field - A wrecking ball taking down an apartment block - An overloaded truck collapsing a truss bridge Outputs: - Opus 5: 55.9K tokens, $1.40 - Fable 5: 55.1K tokens, $2.82 - Kimi K3: 35.7K tokens, $0.55 - GPT 5.6: 20.1K tokens, $0.31 Opus got all three right unlike the other models. Houses fly up the funnel and out the top, the wall breaks where the ball hits and the rubble piles up, the bridge drops the truck into the river. Fable had almost nothing on the ground for the tornado to pick up, its building collapsed on its own before the ball even touched it and its bridge blew into sticks all at once. GPT is the cheapest here but its ball never reached the building at all and its bridge fell apart in a way nothing falls apart in real life. Kimi K3, the new Chinese frontier model, ended up in the same place as GPT
0:22

Opus 5 crushed Fable 5 at 3D destruction physics for 2x cheaper! We gave four models the same task: build three self-contained HTML scenes with real physics Prompts: - A tornado that sucks in a whole field - A wrecking ball taking down an apartment block - An overloaded truck collapsing a truss bridge Outputs: - Opus 5: 55.9K tokens, $1.40 - Fable 5: 55.1K tokens, $2.82 - Kimi K3: 35.7K tokens, $0.55 - GPT 5.6: 20.1K tokens, $0.31 Opus got all three right unlike the other models. Houses fly up the funnel and out the top, the wall breaks where the ball hits and the rubble piles up, the bridge drops the truck into the river. Fable had almost nothing on the ground for the tornado to pick up, its building collapsed on its own before the ball even touched it and its bridge blew into sticks all at once. GPT is the cheapest here but its ball never reached the building at all and its bridge fell apart in a way nothing falls apart in real life. Kimi K3, the new Chinese frontier model, ended up in the same place as GPT

atomic.chat

1,418,720 views • 1 day ago

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.
0:30

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

31,964 views • 8 days ago

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
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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.

2,142,570 views • 9 days ago