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Opus 4.6 vs Gemini Pro 3.1 (7/9) I wanted to do a physics simulation test, overall both models did a good job in this department, however Opus added nice animations to things like "Fan", "Magnet" whilst gemini just rendered them out as a red circle. Opus also included way...

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Dev Ed

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28,179 次观看 • 5 个月前 •via X (Twitter)

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Opus 4.6 vs Gemini 3 Pro (3/9) prompt: Build a premium interactive isometric 3D cozy room using Vite + React + Three.js (react-three-fiber/drei), with all objects modeled in code (no external assets) and subtle ambient animations. Gemini looks good on initial impression but I feel like I have way more to work with opus here (opus also did light/dark mode and took a quarter of the time to make it).
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Opus 4.6 vs Gemini 3 Pro (3/9) prompt: Build a premium interactive isometric 3D cozy room using Vite + React + Three.js (react-three-fiber/drei), with all objects modeled in code (no external assets) and subtle ambient animations. Gemini looks good on initial impression but I feel like I have way more to work with opus here (opus also did light/dark mode and took a quarter of the time to make it).

Dev Ed

77,206 次观看 • 6 个月前

Opus 4.6 vs GPT-5.4 (High) (6/9) Testing out how well these models to with cloth physics simulation, and honestly both where pretty close here but my god I am shocked how good GPT 5.4 is with optimizing this scene whilst opus 4.6 felt quite janky and lower fps. GPT 5.4 also got the cutting working properly whilst Opus was just floating about. I do want to heavily stress the fact that making this prompt, Opus 4.6 cost the whole 100% of the session ($20 pro plan) + $3 in credits whilst GPT 5.4 only cost 10% of the usage. prompt: Build a premium Vite + React interactive cloth simulation of a cozy room curtain using real particle/constraint physics, with structural + shear springs, damping, collisions, and stable real-time deformation. Users should be able to drag the curtain, add wind, and cut constraints, while the experience stays polished, visually elegant, and numerically stable.
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Opus 4.6 vs GPT-5.4 (High) (6/9) Testing out how well these models to with cloth physics simulation, and honestly both where pretty close here but my god I am shocked how good GPT 5.4 is with optimizing this scene whilst opus 4.6 felt quite janky and lower fps. GPT 5.4 also got the cutting working properly whilst Opus was just floating about. I do want to heavily stress the fact that making this prompt, Opus 4.6 cost the whole 100% of the session ($20 pro plan) + $3 in credits whilst GPT 5.4 only cost 10% of the usage. prompt: Build a premium Vite + React interactive cloth simulation of a cozy room curtain using real particle/constraint physics, with structural + shear springs, damping, collisions, and stable real-time deformation. Users should be able to drag the curtain, add wind, and cut constraints, while the experience stays polished, visually elegant, and numerically stable.

Dev Ed

414,381 次观看 • 5 个月前

Opus 4.6 vs Gemini Pro 3.1 (5/9) Opus absolutely COOKS gemini, by creating an overall better cohesive design, extra features like like dark mode, poper tabs for stock analysis, news, and it even created it's own svgs for the stock tickers whilst doing it FASTER than gemini. Opus: 12 mins 23 seconds Gemini: 18 mins 31 seconds (had to reprompt it 3 extra times to fix syntax errors) prompt: Build a high-end stock analysis dashboard using React + Vite + TypeScript, with a polished TradingView/Bloomberg-style UI, left sidebar of stock tickers, smooth transitions, and premium charts (candlesticks, indicators, comparisons). Use local dummy JSON data only (prices, financials, future points) with a time-simulation mode, rich stock detail tabs (overview, financials, valuation, technicals), and add 3–5 pro features like watchlists, compare mode, alerts, portfolio sandbox, or earnings calendar—architected so a real API can be swapped in later.
0:54

Opus 4.6 vs Gemini Pro 3.1 (5/9) Opus absolutely COOKS gemini, by creating an overall better cohesive design, extra features like like dark mode, poper tabs for stock analysis, news, and it even created it's own svgs for the stock tickers whilst doing it FASTER than gemini. Opus: 12 mins 23 seconds Gemini: 18 mins 31 seconds (had to reprompt it 3 extra times to fix syntax errors) prompt: Build a high-end stock analysis dashboard using React + Vite + TypeScript, with a polished TradingView/Bloomberg-style UI, left sidebar of stock tickers, smooth transitions, and premium charts (candlesticks, indicators, comparisons). Use local dummy JSON data only (prices, financials, future points) with a time-simulation mode, rich stock detail tabs (overview, financials, valuation, technicals), and add 3–5 pro features like watchlists, compare mode, alerts, portfolio sandbox, or earnings calendar—architected so a real API can be swapped in later.

Dev Ed

286,780 次观看 • 5 个月前

New Fable 5 beats Opus 4.8 on real world physics simulations We gave both models the same three prompts and asked them to build self contained HTML5 sims with real physics and no libraries: 1. Chaotic double pendulum 2. Galton board 3. Water in a spinning drum (WCSPH) Generation cost Fable 5: $3.35 on 68.7k tokens, time 14m 47s Opus 4.8: $0.93 on 38.9k tokens, time 8m 10s Fable clearly did better on the water simulation, producing a much more solid and continuous body of water. Opus left larger gaps near the walls, scattered particles around the scene, and struggled to keep the fluid stable.
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New Fable 5 beats Opus 4.8 on real world physics simulations We gave both models the same three prompts and asked them to build self contained HTML5 sims with real physics and no libraries: 1. Chaotic double pendulum 2. Galton board 3. Water in a spinning drum (WCSPH) Generation cost Fable 5: $3.35 on 68.7k tokens, time 14m 47s Opus 4.8: $0.93 on 38.9k tokens, time 8m 10s Fable clearly did better on the water simulation, producing a much more solid and continuous body of water. Opus left larger gaps near the walls, scattered particles around the scene, and struggled to keep the fluid stable.

atomic.chat

1,587,762 次观看 • 2 个月前

Introducing Agent Mode: Agentic AI is now measured in the Arena. Agent Mode can do deep research, create reports, generate images, build websites, debug code, and more. It completes more complex tasks by using tools like web search, bash in a sandbox environment, image generation, file writing, and asking follow-up questions. Frontier models are waiting for you in Agent Mode to take on real-world tasks. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and top open models. Test them yourself.
0:44

Introducing Agent Mode: Agentic AI is now measured in the Arena. Agent Mode can do deep research, create reports, generate images, build websites, debug code, and more. It completes more complex tasks by using tools like web search, bash in a sandbox environment, image generation, file writing, and asking follow-up questions. Frontier models are waiting for you in Agent Mode to take on real-world tasks. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and top open models. Test them yourself.

Arena.ai

432,185 次观看 • 2 个月前

Testing the new Claude Opus 4.6 vs. Gemini 3 Pro on Sider’s Artifacts! 🚀 I love turning complex articles into "interactive reading" to boost my efficiency. With the new Claude Opus 4.6 out, I ran a head-to-head comparison. Here's the breakdown: 1/ Gemini 3 Pro: The "Gamified" Experience 🎮 The interface is incredibly clean and minimalist, but the real magic is the interactivity. It’s highly engaging and fun—honestly, it feels like playing a game. It turns passive reading into an active exploration where you actually enjoy clicking through the content. 2/ Claude Opus 4.6: The "High-Tech" Analyst 🧠 The visuals are dazzling—it has a super cool, futuristic vibe. But beyond the look, the breakdown is insanely detailed. It dissects complex concepts from multiple granular angles. It feels like examining the DNA of the article. The Verdict: Choose Gemini 3 Pro for a clean layout with a fun, game-like vibe. Choose Claude Opus 4.6 for "cooler" visuals and superior, microscopic content breakdown. Both are game-changers for "chewing" through difficult papers! 📖✨ Which style do you prefer?
0:39

Testing the new Claude Opus 4.6 vs. Gemini 3 Pro on Sider’s Artifacts! 🚀 I love turning complex articles into "interactive reading" to boost my efficiency. With the new Claude Opus 4.6 out, I ran a head-to-head comparison. Here's the breakdown: 1/ Gemini 3 Pro: The "Gamified" Experience 🎮 The interface is incredibly clean and minimalist, but the real magic is the interactivity. It’s highly engaging and fun—honestly, it feels like playing a game. It turns passive reading into an active exploration where you actually enjoy clicking through the content. 2/ Claude Opus 4.6: The "High-Tech" Analyst 🧠 The visuals are dazzling—it has a super cool, futuristic vibe. But beyond the look, the breakdown is insanely detailed. It dissects complex concepts from multiple granular angles. It feels like examining the DNA of the article. The Verdict: Choose Gemini 3 Pro for a clean layout with a fun, game-like vibe. Choose Claude Opus 4.6 for "cooler" visuals and superior, microscopic content breakdown. Both are game-changers for "chewing" through difficult papers! 📖✨ Which style do you prefer?

Ace

109,206 次观看 • 6 个月前

fable, I want you to grab a MetaHuman file off of Unreal Engine Marketplace or Fab Marketplace or something like that. There should be free ones. Find a character controller that works with that for web and threeJS. Specifically for flying, like Superman, generate a World Labs outdoor environment of your choosing and set up a threeJS project where we can fly around with a character like Superman, with really nice flying animations, camera animations, and camera zoom and shake effects when you're flying. Put some nice post-processing on it with some bloom and grain and stuff like that. Really just make this feel as polished as you can, where we get to fly around in a world where the flight feels similar to Superman. Do it in one shot and without any input from me. optimize it 2 prompts - NOT BAD!! Honestly could get this feeling/looking 10x better with probably 2 more prompts. I'd likely use a larger city GLB, populate the outskirts with World Labs gsplats, manually grab a better character to use, and add some objectives. But I wanted to see what it could do in 1 prompt (basically) Try it out 👇
0:38

fable, I want you to grab a MetaHuman file off of Unreal Engine Marketplace or Fab Marketplace or something like that. There should be free ones. Find a character controller that works with that for web and threeJS. Specifically for flying, like Superman, generate a World Labs outdoor environment of your choosing and set up a threeJS project where we can fly around with a character like Superman, with really nice flying animations, camera animations, and camera zoom and shake effects when you're flying. Put some nice post-processing on it with some bloom and grain and stuff like that. Really just make this feel as polished as you can, where we get to fly around in a world where the flight feels similar to Superman. Do it in one shot and without any input from me. optimize it 2 prompts - NOT BAD!! Honestly could get this feeling/looking 10x better with probably 2 more prompts. I'd likely use a larger city GLB, populate the outskirts with World Labs gsplats, manually grab a better character to use, and add some objectives. But I wanted to see what it could do in 1 prompt (basically) Try it out 👇

Nicholas | WithLore

88,652 次观看 • 2 个月前

Opus 5 DID NOT 1 shot this paper sketch style multiplayer FPS game, with highly satisfying shooting mechanics. Been seeing all these "look at Opus 1 shotted" demos, tried the public prompts on Ultracode, and what it produces is a stuff of nightmares, worthy only of a selective screen recording for X. These are cool capability tests, but not games. I've been building this black/white themed high action and performance FPS that feels good to play for the last week or so . This was done as a series of ~100 prompts using Fable 5, Sol, Grok 4.5 and now Opus 5, over the course of ~20 hrs. I would not say Opus 5 is a "game changer", but its noticeably better, and sometimes faster. The demo video below is local sandbox mode, but 64hz LAN multiplayer works pretty well too. Ported over some Counterstrike maps (dust and assault), if you're into classics. Source code below. Run it with 3 commands.
1:30

Opus 5 DID NOT 1 shot this paper sketch style multiplayer FPS game, with highly satisfying shooting mechanics. Been seeing all these "look at Opus 1 shotted" demos, tried the public prompts on Ultracode, and what it produces is a stuff of nightmares, worthy only of a selective screen recording for X. These are cool capability tests, but not games. I've been building this black/white themed high action and performance FPS that feels good to play for the last week or so . This was done as a series of ~100 prompts using Fable 5, Sol, Grok 4.5 and now Opus 5, over the course of ~20 hrs. I would not say Opus 5 is a "game changer", but its noticeably better, and sometimes faster. The demo video below is local sandbox mode, but 64hz LAN multiplayer works pretty well too. Ported over some Counterstrike maps (dust and assault), if you're into classics. Source code below. Run it with 3 commands.

Yegor Sak

25,479 次观看 • 24 天前

Over the weekend, I added multiplayer "paint ball" dogfight to Tiny Skies, so players can fly around pelting each other with colourful paint balls, just for fun. I tried meshy and tripo to generate some 3D models for the game and the mesh vertices count are really high and lags the game a lot (probably because my game is a globe with thousands of objects - albeit mostly instanced). To my surprise, I found Gemini 3.1 Pro to be really quite good at generating good looking 3D models that are low in poly count. It generated 3D models at a much higher quality than Opus 4.6, Sonnet 4.6 and GPT 5.4. You can see the upgraded biplane models and some objects in the video below. #vibejam
0:23

Over the weekend, I added multiplayer "paint ball" dogfight to Tiny Skies, so players can fly around pelting each other with colourful paint balls, just for fun. I tried meshy and tripo to generate some 3D models for the game and the mesh vertices count are really high and lags the game a lot (probably because my game is a globe with thousands of objects - albeit mostly instanced). To my surprise, I found Gemini 3.1 Pro to be really quite good at generating good looking 3D models that are low in poly count. It generated 3D models at a much higher quality than Opus 4.6, Sonnet 4.6 and GPT 5.4. You can see the upgraded biplane models and some objects in the video below. #vibejam

Danny Limanseta

36,419 次观看 • 4 个月前

🚨 JUST IN: Claude got a huge update today and I'm flattered to be a part of it. As of now, Claude Opus 4.6 can build mobile apps and prepare shipping them on the Apple + Google app stores. We just launched Shipper a new package that empowers Claude to: → Build complete mobile apps → Recreate existing apps → Assure iOS & Android compatibility → Autofill listings for both app stores (app icon, images, descriptions, keywords, privacy policy etc) Claude Opus 4.6 can do all of the above in one prompt for ~$0.17/app... Publishable from the first prompt & built in 5 mins, not months. You can try it on Shipper by asking Claude to "create an AI chatbot like Perplexity" or "eBay style marketplace app for local goods". To celebrate this huge step forward, if you comment "SHIP" you will get free credits.
0:44

🚨 JUST IN: Claude got a huge update today and I'm flattered to be a part of it. As of now, Claude Opus 4.6 can build mobile apps and prepare shipping them on the Apple + Google app stores. We just launched Shipper a new package that empowers Claude to: → Build complete mobile apps → Recreate existing apps → Assure iOS & Android compatibility → Autofill listings for both app stores (app icon, images, descriptions, keywords, privacy policy etc) Claude Opus 4.6 can do all of the above in one prompt for ~$0.17/app... Publishable from the first prompt & built in 5 mins, not months. You can try it on Shipper by asking Claude to "create an AI chatbot like Perplexity" or "eBay style marketplace app for local goods". To celebrate this huge step forward, if you comment "SHIP" you will get free credits.

David Ch

448,999 次观看 • 6 个月前

GPT-5.6 Sol Ultra lost to GPT-5.5 on physics at 3× the cost! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: - A monster truck backflipping onto a parked car - A stunt car jumping six buses into a brick wall - A train derailing off a broken bridge into the water Outputs: GPT-5.6 Sol Ultra: 32.9K tokens, $0.33 Opus 4.8: 9.2K tokens, $0.24 GPT-5.5: 12.4K tokens, $0.11 Grok 4.5: 7.0K tokens, $0.08 Sol Ultra draws just like GPT-5.5, only with more detail and it shows clearest on the bus jump where the two look almost identical. In the other tests Sol Ultra came out worse than its predecessor and the physics really got weaker. We think GPT-5.5 took the truck flip and the train outright. With Sol Ultra you basically get GPT-5.5 with weaker physics and a nicer picture for 3x the price. Newborn Grok 4.5 failed two of the three tests and only came good on the train
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GPT-5.6 Sol Ultra lost to GPT-5.5 on physics at 3× the cost! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: - A monster truck backflipping onto a parked car - A stunt car jumping six buses into a brick wall - A train derailing off a broken bridge into the water Outputs: GPT-5.6 Sol Ultra: 32.9K tokens, $0.33 Opus 4.8: 9.2K tokens, $0.24 GPT-5.5: 12.4K tokens, $0.11 Grok 4.5: 7.0K tokens, $0.08 Sol Ultra draws just like GPT-5.5, only with more detail and it shows clearest on the bus jump where the two look almost identical. In the other tests Sol Ultra came out worse than its predecessor and the physics really got weaker. We think GPT-5.5 took the truck flip and the train outright. With Sol Ultra you basically get GPT-5.5 with weaker physics and a nicer picture for 3x the price. Newborn Grok 4.5 failed two of the three tests and only came good on the train

atomic.chat

896,867 次观看 • 1 个月前

GEMINI 3 LAUNCH IS HERE I got a SNEAK PEEK at Gemini 3 with Logan Kilpatrick (Google Deepmind), and it might be the most POWERFUL vibe-coding tool on the planet. A little breakdown: 1. Anyone can build 3D and casual games now You can vibecode full, playable 3D video games generated in minutes. Actual games with physics, characters, controls, and loops you can remix instantly. Pure insanity. I can see founders and brands spinning up games on the fly to ride trends and drive growth. 2. Intelligent apps are becoming the default We built apps where reasoning, memory, and multi-step planning were baked in from the start. Once you’re building apps with ACTUAL intelligence baked in, there’s a whole wave of new opportunities that weren’t possible before. 3. Gemini acts like a creative partner You describe the idea, Gemini fills in the gaps, challenges decisions, proposes alternatives, and iterates in real time. 4. Vibe coding hits a new level Gemini 3 can generate assets, code, game logic, UI, and narrative in one flow. Tools like Claude and Cursor feel fast. This feels like the next layer, the one where a single builder can compete with full teams. Logan Kilpatrick and I pushed Google Gemini 3 hard, and the outputs were solid. A few times we had to give it a few extra prompts but it took feedback really well. I think 1 year ago, a lot of people discounted Google in the AI arms race. Can you discount them anymore? Doubt it. After this, it feels like they at best leading, at worst leading. What do you think of Google's AI efforts/Gemini 3 My biggest takeaway was how it just felt like Gemini 3 had a little more vibe coding horsepower than anything I’ve used.
39:03

GEMINI 3 LAUNCH IS HERE I got a SNEAK PEEK at Gemini 3 with Logan Kilpatrick (Google Deepmind), and it might be the most POWERFUL vibe-coding tool on the planet. A little breakdown: 1. Anyone can build 3D and casual games now You can vibecode full, playable 3D video games generated in minutes. Actual games with physics, characters, controls, and loops you can remix instantly. Pure insanity. I can see founders and brands spinning up games on the fly to ride trends and drive growth. 2. Intelligent apps are becoming the default We built apps where reasoning, memory, and multi-step planning were baked in from the start. Once you’re building apps with ACTUAL intelligence baked in, there’s a whole wave of new opportunities that weren’t possible before. 3. Gemini acts like a creative partner You describe the idea, Gemini fills in the gaps, challenges decisions, proposes alternatives, and iterates in real time. 4. Vibe coding hits a new level Gemini 3 can generate assets, code, game logic, UI, and narrative in one flow. Tools like Claude and Cursor feel fast. This feels like the next layer, the one where a single builder can compete with full teams. Logan Kilpatrick and I pushed Google Gemini 3 hard, and the outputs were solid. A few times we had to give it a few extra prompts but it took feedback really well. I think 1 year ago, a lot of people discounted Google in the AI arms race. Can you discount them anymore? Doubt it. After this, it feels like they at best leading, at worst leading. What do you think of Google's AI efforts/Gemini 3 My biggest takeaway was how it just felt like Gemini 3 had a little more vibe coding horsepower than anything I’ve used.

GREG ISENBERG

73,705 次观看 • 9 个月前

I just compared Claude Code vs Codex vs Cursor CLI The task was to build a Next.js app with Tailwind 4 and shadcn components to collect customer feedback and showcase it with a widget. I gave all three the same prompt and let them go for 30 minutes to see what they came up with. Claude Code with Opus 4.1 Even though I told it to set up the app in the existing project folder, it tried to create a directory for it. After I interrupted and told it not to do that, it built a demo form and landing page with no errors. I had to ask it to make the demo interactive so users could submit a testimonial and preview it. The landing page looked like AI and was pretty basic, but it worked and it was done in a fraction of the time of the others. Total tokens used: 33k Codex with GPT-5 At the end of the 30 minutes I just could not get Codex to produce a working app. It got stuck in a loop of not being able to set up Tailwind 4 and despite many, MANY, attempts, I ended up with a "failed to compile" error. Total tokens used: 102k Cursor Agent with GPT-5 This was the slowest agent by far and a couple of times I actually thought it got stuck in a loop and was close to Ctrl+C'ing to cancel it. The TUI is really nice though, especially how it shows diffs and it did eventually build a working app (after one or two slight errors that needed fixing) The demo was interactive and it had a very minimal design that looked bare but also a lot less like an "AI generated" app than the Opus 4.1 design. It also wasn't too chatty and just did what it needed to do! Code quality was on a par with Opus 4.1, but it did use 5.5x as many tokens to get there. Still cheaper than Opus on a direct comparison but not when you factor in a Claude Code Max subscription. Total tokens: 188k I'll be able to do a proper comparison and record some videos when I'm back from holiday but for now, Opus is still the more capable model out of the box and Claude Code is the more complete CLI product. It will be interesting to see how Cursor evolve their CLI though with commands and subagents because I think with GPT-5 they have a real shot at providing competition for Claude Code if they can optimise output to get similar quality with less tokens. Jump to 0:40 in the video to see the two apps. Which do you think is which? ;)
1:18

I just compared Claude Code vs Codex vs Cursor CLI The task was to build a Next.js app with Tailwind 4 and shadcn components to collect customer feedback and showcase it with a widget. I gave all three the same prompt and let them go for 30 minutes to see what they came up with. Claude Code with Opus 4.1 Even though I told it to set up the app in the existing project folder, it tried to create a directory for it. After I interrupted and told it not to do that, it built a demo form and landing page with no errors. I had to ask it to make the demo interactive so users could submit a testimonial and preview it. The landing page looked like AI and was pretty basic, but it worked and it was done in a fraction of the time of the others. Total tokens used: 33k Codex with GPT-5 At the end of the 30 minutes I just could not get Codex to produce a working app. It got stuck in a loop of not being able to set up Tailwind 4 and despite many, MANY, attempts, I ended up with a "failed to compile" error. Total tokens used: 102k Cursor Agent with GPT-5 This was the slowest agent by far and a couple of times I actually thought it got stuck in a loop and was close to Ctrl+C'ing to cancel it. The TUI is really nice though, especially how it shows diffs and it did eventually build a working app (after one or two slight errors that needed fixing) The demo was interactive and it had a very minimal design that looked bare but also a lot less like an "AI generated" app than the Opus 4.1 design. It also wasn't too chatty and just did what it needed to do! Code quality was on a par with Opus 4.1, but it did use 5.5x as many tokens to get there. Still cheaper than Opus on a direct comparison but not when you factor in a Claude Code Max subscription. Total tokens: 188k I'll be able to do a proper comparison and record some videos when I'm back from holiday but for now, Opus is still the more capable model out of the box and Claude Code is the more complete CLI product. It will be interesting to see how Cursor evolve their CLI though with commands and subagents because I think with GPT-5 they have a real shot at providing competition for Claude Code if they can optimise output to get similar quality with less tokens. Jump to 0:40 in the video to see the two apps. Which do you think is which? ;)

Ian Nuttall

194,949 次观看 • 1 年前

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

1,479,831 次观看 • 26 天前

This is one of the wildest things I have built with AI so far 😱 Asked Claude Fable 5 to create a fully interactive 3D crime investigation board using Three.js and it did it in ONE Prompt. It took one more prompt to give it a polished UI inspired by a reference design that I created with GPT Image. What surprised me most was not how it looked. It was how it worked. Fable built a complete Verlet rope physics system with 46 particles in every thread. It handled gravity, damping, distance constraints and all other features of file upload, text and everything. The threads/ropes even lift naturally with pinned evidence instead of clipping through it. I never asked it to implement any of that. I only described the experience I wanted. Maybe that's how we should work with AI. Instead of writing long long specs, we should explain what we want as an experience and let AI do its thing. Anyway, every day Fable 5 raises the bar for what I think AI can build. More to this Live: Code:
0:49

This is one of the wildest things I have built with AI so far 😱 Asked Claude Fable 5 to create a fully interactive 3D crime investigation board using Three.js and it did it in ONE Prompt. It took one more prompt to give it a polished UI inspired by a reference design that I created with GPT Image. What surprised me most was not how it looked. It was how it worked. Fable built a complete Verlet rope physics system with 46 particles in every thread. It handled gravity, damping, distance constraints and all other features of file upload, text and everything. The threads/ropes even lift naturally with pinned evidence instead of clipping through it. I never asked it to implement any of that. I only described the experience I wanted. Maybe that's how we should work with AI. Instead of writing long long specs, we should explain what we want as an experience and let AI do its thing. Anyway, every day Fable 5 raises the bar for what I think AI can build. More to this Live: Code:

The Bugged Dev

103,991 次观看 • 1 个月前

Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. We gave Gemini sequences of different modalities — image and text in this case — and had it respond by predicting what might come next. Devs can try similar things when access to Pro opens on 12/13 🚀. The knitting demo used Ultra⚡ All the user prompts and outputs in the video are real, shortened for brevity. The video illustrates what the multimodal user experiences built with Gemini could look like. We made it to inspire developers. When you’re building an app, you can get similar results (there’s always some variability with LLMs) by prompting Gemini with an instruction that allows the user to "configure" the behavior of the model, like inputting “you are an expert in science …” before a user can engage in the same kind of back and forth dialogue. Here’s a clip of what this looks like in AI Studio with Gemini Pro. We’ve come a long way since Flamingo 🦩 & PALI, looking forward to seeing what people build with it!
2:24

Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. We gave Gemini sequences of different modalities — image and text in this case — and had it respond by predicting what might come next. Devs can try similar things when access to Pro opens on 12/13 🚀. The knitting demo used Ultra⚡ All the user prompts and outputs in the video are real, shortened for brevity. The video illustrates what the multimodal user experiences built with Gemini could look like. We made it to inspire developers. When you’re building an app, you can get similar results (there’s always some variability with LLMs) by prompting Gemini with an instruction that allows the user to "configure" the behavior of the model, like inputting “you are an expert in science …” before a user can engage in the same kind of back and forth dialogue. Here’s a clip of what this looks like in AI Studio with Gemini Pro. We’ve come a long way since Flamingo 🦩 & PALI, looking forward to seeing what people build with it!

Oriol Vinyals

180,991 次观看 • 2 年前

sonnet 5 vs sonnet 4.6 vs opus 4.8 vs glm 5.2 – frontend tasks dropped sonnet 5 into a quick test today. same three prompts to all four models, single-shot html/canvas, no edits: • objects falling on a trampoline • rockets playing tennis • a slingshot breaking bottles ranked by speed (total across the 3 tasks): 1. opus 4.8 – 15m 09s 2. sonnet 5 – 16m 05s 3. glm 5.2 – 27m 18s 4. sonnet 4.6 – 35m 06s ranked by code shortness (total loc): 1. sonnet 5 – 1794 2. opus 4.8 – 2063 3. sonnet 4.6 – 2182 4. glm 5.2 – 3285 sonnet 5 came out on top here – leanest code overall and a near-tie for fastest it was also the most creative. in every task it added something none of the others did: – kept the trampoline vibrating after the objects landed – drew a +1 next to the rocket that scored the point – turned the slingshot to face the next bottle before each shot opus 4.8 evaluated the code sonnet 5 produced. four things stood out: • the sphere is a fake, and that's the smart move. the cube and star are real 3d meshes with proper culling and shading, but the ball is just a flat shaded circle. a lit sphere looks identical from every angle, so building it in 3d would burn compute for zero visible payoff. knowing where not to bother is its own kind of skill • weight actually means something on the trampoline. the star is heavy, so it barely bounces and dents the mat hard. the ball is light, so it's lively and leaves a shallow dip. the three objects aren't just different shapes – they have different temperaments, and the physics is what gives them that • the slingshot is framed like a shot, not just drawn. the handle is anchored below the bottom of the screen and runs off-frame, so it reads as something you're holding rather than a sprite parked in the scene. that's a staging instinct, not a rendering one • the paddle ai forward-simulates the ball to predict where it'll land, then adds a deliberate error bias (roughly 1 in 5 shots is a real miss). that's why scoring looks natural instead of robotic – plus four distinct fault types with a catch-all so a rally never hangs without a result bottom line: sonnet 5 does more with less. fastest tier, leanest code, and the only one that added small touches nobody asked for follow thehype. for 24/7 ai news, analysis and breakdowns
0:37

sonnet 5 vs sonnet 4.6 vs opus 4.8 vs glm 5.2 – frontend tasks dropped sonnet 5 into a quick test today. same three prompts to all four models, single-shot html/canvas, no edits: • objects falling on a trampoline • rockets playing tennis • a slingshot breaking bottles ranked by speed (total across the 3 tasks): 1. opus 4.8 – 15m 09s 2. sonnet 5 – 16m 05s 3. glm 5.2 – 27m 18s 4. sonnet 4.6 – 35m 06s ranked by code shortness (total loc): 1. sonnet 5 – 1794 2. opus 4.8 – 2063 3. sonnet 4.6 – 2182 4. glm 5.2 – 3285 sonnet 5 came out on top here – leanest code overall and a near-tie for fastest it was also the most creative. in every task it added something none of the others did: – kept the trampoline vibrating after the objects landed – drew a +1 next to the rocket that scored the point – turned the slingshot to face the next bottle before each shot opus 4.8 evaluated the code sonnet 5 produced. four things stood out: • the sphere is a fake, and that's the smart move. the cube and star are real 3d meshes with proper culling and shading, but the ball is just a flat shaded circle. a lit sphere looks identical from every angle, so building it in 3d would burn compute for zero visible payoff. knowing where not to bother is its own kind of skill • weight actually means something on the trampoline. the star is heavy, so it barely bounces and dents the mat hard. the ball is light, so it's lively and leaves a shallow dip. the three objects aren't just different shapes – they have different temperaments, and the physics is what gives them that • the slingshot is framed like a shot, not just drawn. the handle is anchored below the bottom of the screen and runs off-frame, so it reads as something you're holding rather than a sprite parked in the scene. that's a staging instinct, not a rendering one • the paddle ai forward-simulates the ball to predict where it'll land, then adds a deliberate error bias (roughly 1 in 5 shots is a real miss). that's why scoring looks natural instead of robotic – plus four distinct fault types with a catch-all so a rally never hangs without a result bottom line: sonnet 5 does more with less. fastest tier, leanest code, and the only one that added small touches nobody asked for follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

14,518 次观看 • 1 个月前

Gemini 2.5 Flash demolishes my Galton Board test, I could not get 4omini, 4o mini high, or 03 to produce this. I found that Gemini 2.5 Flash understands my intents almost instantly, code produced is tight and neat. The prompt is a merging of various steps. It took me 5 steps to achieve this in Gemini 2.5 Flash, I gave up on OpenAI models after about half an hour. My iterations are obviously not exact. But people can test with this one prompt for more objective comparison. Please try this prompt on your end to confirm: -------------------------------------------------- Create a self-contained HTML file for a Galton board simulation using client-side JavaScript and a 2D physics engine (like Matter.js, included via CDN). The simulation should be rendered on an HTML5 canvas and meet the following criteria: 1. **Single File:** All necessary HTML, CSS, and JavaScript code must be within this single `.html` file. 2. **Canvas Size:** The overall simulation area (canvas) should be reasonably sized to fit on a standard screen without requiring extensive scrolling or zooming (e.g., around 500x700 pixels). 3. **Physics:** Utilize a 2D rigid body physics engine for realistic ball-peg and ball-wall interactions. 4. **Obstacles (Pegs):** Create static, circular pegs arranged in full-width horizontal rows extending across the usable width of the board (not just a triangle). The pegs should be small enough and spaced appropriately for balls to navigate and bounce between them. 5. **Containment:** * Include static, sufficiently thick side walls and a ground at the bottom to contain the balls within the board. * Implement *physical* static dividers between the collection bins at the bottom. These dividers must be thick enough to prevent balls from passing through them, ensuring accurate accumulation in each bin. 6. **Ball Dropping:** Balls should be dropped from a controlled, narrow area near the horizontal center at the top of the board to ensure they enter the peg field consistently. 7. **Bins:** The collection area at the bottom should be divided into distinct bins by the physical dividers. The height of the bins should be sufficient to clearly visualize the accumulation of balls. 8. **Visualization:** Use a high-contrast color scheme to clearly distinguish between elements. Specifically, use yellow for the structural elements (walls, top guides, physical bin dividers, ground), a contrasting color (like red) for the pegs, and a highly contrasting color (like dark grey or black) for the balls. 9. **Demonstration:** The simulation should visually demonstrate the formation of the normal (or binomial) distribution as multiple balls fall through the pegs and collect in the bins. Ensure the physics parameters (restitution, friction, density) and ball drop rate are tuned for a smooth and clear demonstration of the distribution. #OpenAI Sam Altman Greg Brockman AshutoshShrivastava Aidan McLaughlin
0:44

Gemini 2.5 Flash demolishes my Galton Board test, I could not get 4omini, 4o mini high, or 03 to produce this. I found that Gemini 2.5 Flash understands my intents almost instantly, code produced is tight and neat. The prompt is a merging of various steps. It took me 5 steps to achieve this in Gemini 2.5 Flash, I gave up on OpenAI models after about half an hour. My iterations are obviously not exact. But people can test with this one prompt for more objective comparison. Please try this prompt on your end to confirm: -------------------------------------------------- Create a self-contained HTML file for a Galton board simulation using client-side JavaScript and a 2D physics engine (like Matter.js, included via CDN). The simulation should be rendered on an HTML5 canvas and meet the following criteria: 1. **Single File:** All necessary HTML, CSS, and JavaScript code must be within this single `.html` file. 2. **Canvas Size:** The overall simulation area (canvas) should be reasonably sized to fit on a standard screen without requiring extensive scrolling or zooming (e.g., around 500x700 pixels). 3. **Physics:** Utilize a 2D rigid body physics engine for realistic ball-peg and ball-wall interactions. 4. **Obstacles (Pegs):** Create static, circular pegs arranged in full-width horizontal rows extending across the usable width of the board (not just a triangle). The pegs should be small enough and spaced appropriately for balls to navigate and bounce between them. 5. **Containment:** * Include static, sufficiently thick side walls and a ground at the bottom to contain the balls within the board. * Implement *physical* static dividers between the collection bins at the bottom. These dividers must be thick enough to prevent balls from passing through them, ensuring accurate accumulation in each bin. 6. **Ball Dropping:** Balls should be dropped from a controlled, narrow area near the horizontal center at the top of the board to ensure they enter the peg field consistently. 7. **Bins:** The collection area at the bottom should be divided into distinct bins by the physical dividers. The height of the bins should be sufficient to clearly visualize the accumulation of balls. 8. **Visualization:** Use a high-contrast color scheme to clearly distinguish between elements. Specifically, use yellow for the structural elements (walls, top guides, physical bin dividers, ground), a contrasting color (like red) for the pegs, and a highly contrasting color (like dark grey or black) for the balls. 9. **Demonstration:** The simulation should visually demonstrate the formation of the normal (or binomial) distribution as multiple balls fall through the pegs and collect in the bins. Ensure the physics parameters (restitution, friction, density) and ball drop rate are tuned for a smooth and clear demonstration of the distribution. #OpenAI Sam Altman Greg Brockman AshutoshShrivastava Aidan McLaughlin

RameshR

247,923 次观看 • 1 年前

⚡ My first advanced simulation with Grok 3! Finally your OS windows act like REAL windows 🤣 As you know, I've spent more than 2 years sharing all kinds of simulations and mini-games made with Claude, ChatGPT (o3-mini-high), etc. It’s been ages since I last wrote a single line of code. But pretty often, once you hit over 1,000 lines, it turns into a debate against the LLM and you frequently get stuck in a loop that’s hard to break out of. Everyone was raving about Grok 3’s ability to generate code, but until now, I hadn’t really put it to the test. So I decided to challenge it with a prompt that both ChatGPT and Claude were seriously struggling with (debate loop). The initial prompt was: "Use Python and a 2D physics library to create a world where I can generate different static objects like squares, triangles, circles and rectangles. I should be able to move them with the mouse, rotate, scale, and delete them. The cool part is that we’ll see this world through 1 to N operating system windows. In other words, the windows will be like real windows! When one of these windows is active and I hit the spacebar, balls affected by physics should appear and interact with the static objects. You can start with placeholders, but later I'll send you a series of PNG images so they all become beautiful sprites." After a few iterations, I got the result you see in the video. Insane, right? 🤯 Now, with Grok, we have the power to create anything that pops into our mind with just a couple of prompts. It’s mind blowing. Ever since I was 9 and messing around with BASIC on my MSX, I've been hooked on visual simulations... And now I can create them using nothing but natural language. It's f***** amazing that we're living in this historic moment!
2:24

⚡ My first advanced simulation with Grok 3! Finally your OS windows act like REAL windows 🤣 As you know, I've spent more than 2 years sharing all kinds of simulations and mini-games made with Claude, ChatGPT (o3-mini-high), etc. It’s been ages since I last wrote a single line of code. But pretty often, once you hit over 1,000 lines, it turns into a debate against the LLM and you frequently get stuck in a loop that’s hard to break out of. Everyone was raving about Grok 3’s ability to generate code, but until now, I hadn’t really put it to the test. So I decided to challenge it with a prompt that both ChatGPT and Claude were seriously struggling with (debate loop). The initial prompt was: "Use Python and a 2D physics library to create a world where I can generate different static objects like squares, triangles, circles and rectangles. I should be able to move them with the mouse, rotate, scale, and delete them. The cool part is that we’ll see this world through 1 to N operating system windows. In other words, the windows will be like real windows! When one of these windows is active and I hit the spacebar, balls affected by physics should appear and interact with the static objects. You can start with placeholders, but later I'll send you a series of PNG images so they all become beautiful sprites." After a few iterations, I got the result you see in the video. Insane, right? 🤯 Now, with Grok, we have the power to create anything that pops into our mind with just a couple of prompts. It’s mind blowing. Ever since I was 9 and messing around with BASIC on my MSX, I've been hooked on visual simulations... And now I can create them using nothing but natural language. It's f***** amazing that we're living in this historic moment!

Javi Lopez ⛩️

209,470 次观看 • 1 年前

CLAUDE OPUS 4.7 TRANSFORMED MY TRADING. i didn't write a single line of code here's exactly what happened: → day 1: opus 4.7 dropped. i killed all my 4.6 bots. → day 2: asked claude to rebuild them. v2 shipped in 18 min. → day 3: went live with on perps. the 3 things that changed in 4.7: → reads chart + orderflow + news in ONE call it's much faster & more capable. and the models will only get better from here. the bot is not the edge. the speed of iteration is the edge. 4.6 shipped a strategy in 4 days. 4.7 ships in 18 minutes. in our community: we stimulate our traders to automate. because we know, traders who ignore AI will be left behind. bookmark this, start building with OPUS 4.7 asap.
0:27

CLAUDE OPUS 4.7 TRANSFORMED MY TRADING. i didn't write a single line of code here's exactly what happened: → day 1: opus 4.7 dropped. i killed all my 4.6 bots. → day 2: asked claude to rebuild them. v2 shipped in 18 min. → day 3: went live with on perps. the 3 things that changed in 4.7: → reads chart + orderflow + news in ONE call it's much faster & more capable. and the models will only get better from here. the bot is not the edge. the speed of iteration is the edge. 4.6 shipped a strategy in 4 days. 4.7 ships in 18 minutes. in our community: we stimulate our traders to automate. because we know, traders who ignore AI will be left behind. bookmark this, start building with OPUS 4.7 asap.

AlphaCartel

41,471 次观看 • 4 个月前