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Fable 5, first Mythos-class model is live on AI/ML API! We ran a fun test: Opus 4.8 vs Fable 5 are generating a 3D Pokemon. Verdict? Fable 5 is brilliant, fast, and rare as Mew… but Opus is still that nice little guy who does great stuff. 💛 Fable... show more

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560,154 просмотров • 1 месяц назад •via X (Twitter)

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🚨 JUST IN: THE US GOVERNMENT JUST SHUT DOWN CLAUDE FABLE 5 FOR THE ENTIRE WORLD > a national security export control directive. effective immediately > every foreign national on earth - including Anthropic's own engineers who built the model - is now locked out > Fable 5 launched 4 days ago > it's already being classified like a weapons system > Anthropic says it's a misunderstanding > the order doesn't care > Opus 4.8 still runs. Fable 5 and Mythos 5 are gone until further notice AI just got its first export control. it won't be the last

🚨 JUST IN: THE US GOVERNMENT JUST SHUT DOWN CLAUDE FABLE 5 FOR THE ENTIRE WORLD > a national security export control directive. effective immediately > every foreign national on earth - including Anthropic's own engineers who built the model - is now locked out > Fable 5 launched 4 days ago > it's already being classified like a weapons system > Anthropic says it's a misunderstanding > the order doesn't care > Opus 4.8 still runs. Fable 5 and Mythos 5 are gone until further notice AI just got its first export control. it won't be the last

Mr. Buzzoni

51,235 просмотров • 1 месяц назад

Claude Fable 5 is our first generally available Mythos-class model. It ships with new safety classifiers that may flag certain prompts in dual-use domains like cyber and bio. We've added fallbacks: a refused request retries on Claude Opus 4.8 instead of dead-ending.

Claude Fable 5 is our first generally available Mythos-class model. It ships with new safety classifiers that may flag certain prompts in dual-use domains like cyber and bio. We've added fallbacks: a refused request retries on Claude Opus 4.8 instead of dead-ending.

ClaudeDevs

463,707 просмотров • 1 месяц назад

this is f**king dangerous someone figured out how to make Opus 4.8 run on Fable 5's brain with one prompt access to the best model is never guaranteed. It disappeared once already this year. but you can use it forever. here's how: 1. ask Fable 5: "write the operating manual your replacement will run on" (procedures, failure modes, a 5-question self-test) 2. save the output as one .md file and drop it into a new Claude Project as the project instructions 3. switch to Opus 4.8 and now your everyday model runs off the smart one's method, no top-tier price save and bookmark this no matter what full extraction prompt is in the article below: ↓

this is f**king dangerous someone figured out how to make Opus 4.8 run on Fable 5's brain with one prompt access to the best model is never guaranteed. It disappeared once already this year. but you can use it forever. here's how: 1. ask Fable 5: "write the operating manual your replacement will run on" (procedures, failure modes, a 5-question self-test) 2. save the output as one .md file and drop it into a new Claude Project as the project instructions 3. switch to Opus 4.8 and now your everyday model runs off the smart one's method, no top-tier price save and bookmark this no matter what full extraction prompt is in the article below: ↓

Hamza Khalid

32,300 просмотров • 10 дней назад

Fable 5 + Goose Ads is insane – literally a full ad-creative team right in Claude Code. 1. Install the skill: npx gooseworks install --all npx gooseworks login 2. Ask Claude Fable to make ads for your brand. /goose-ads create ads for my brand . Fable 5 pulls the ads already winning in your space and rebuilds them on-brand – your product, your palette, your copy – a whole batch, ready to test. It can ship a month of creative testing in a single prompt. This is also possible with Opus and Sonnet, but Fable's brand research is next level. Link below.

Shiv

208,361 просмотров • 15 дней назад

I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

I tested Kimi K3 vs Claude Opus 4.8 Same prompt, an armory bay with lighting, props, and detail. Top is Kimi K3, bottom is Opus 4.8. It's not even close. Kimi K3 built a full scene with textures, proper lighting, ammo crates, weapon racks, working detail everywhere. Opus 4.8 gave me a near empty room with a couple of floating tables. No doubt it beats Opus 4.8. Kimi K3 is Fable 5 level, and it's clearly better than GPT-5.6 Sol at 3D and games. An open weight model just matched the best closed models on the market. Let that sink in.

Bhavy☄️

437,837 просмотров • 2 дней назад

Fable 5 is now available on Adapt to supercharge your business. We're giving away 60 days of free, unlimited use for qualified business pilots! Adapt's agent connects across all of your company's apps, answers questions and does work all within Slack. We give your business a single brain, shared knowledge for all of your employees. You can now use Fable 5 in your Slack workspace, Anthropic's latest Mythos-class model. Fable 5 exceeds previous model capabilities, accelerating performance in coding, knowledge work, and tool use. We've seen a jump in the quality of Adapt's responses, generation and interpretation of images, writing code for Adapt apps, and more. Excited to have you all try it out. If you're interested in trying out Fable 5 in Adapt, we're giving away 60 days of free unlimited use. Comment below or reach out to us to get started.

Fable 5 is now available on Adapt to supercharge your business. We're giving away 60 days of free, unlimited use for qualified business pilots! Adapt's agent connects across all of your company's apps, answers questions and does work all within Slack. We give your business a single brain, shared knowledge for all of your employees. You can now use Fable 5 in your Slack workspace, Anthropic's latest Mythos-class model. Fable 5 exceeds previous model capabilities, accelerating performance in coding, knowledge work, and tool use. We've seen a jump in the quality of Adapt's responses, generation and interpretation of images, writing code for Adapt apps, and more. Excited to have you all try it out. If you're interested in trying out Fable 5 in Adapt, we're giving away 60 days of free unlimited use. Comment below or reach out to us to get started.

Adapt

414,518 просмотров • 1 месяц назад

Fable 5 comes back！It can now build playable game prototypes. I think it is actually a signal for where AI coding is going. Making a game is not just “write some code.” Even a small browser game needs: game loop；character movement；collision logic；scoring system；UI states；physics tuning；visual feedback；bug fixing；playtesting This is why game prototyping is a great test for AI models. A model cannot fake it with a pretty answer. Either the game runs, or it does not. What impressed me about Fable 5 is that it is useful for the messy middle: turning an idea into mechanics, turning mechanics into code, debugging broken interactions, and iterating until the prototype feels playable. But here is the practical part: I would not use the strongest model for every step. For game building, I would split the workflow: 1. Fable 5 for game design + architecture 2. a fast coding model for routine implementation 3. a vision-capable model for screenshot/UI feedback 4. a cheaper model for docs, test cases, and small fixes 5. fallback when latency, cost, or output quality becomes a problem That is the real AI coding stack. Not “one magic model does everything.” More like: the right model, for the right task, at the right cost, with fallback when things break. This is why I’ve been looking at ZenMux ZenMux. ZenMux gives developers one gateway to access multiple leading AI models, with OpenAI / Anthropic / Google Vertex compatible APIs, cost tracking, quality benchmarks, auto-routing, and compensation when output quality, latency, or throughput falls short. If AI can now make games, the next question is not just “which model is strongest?” It is:how do we manage the whole model workflow Fable 5 shows the creative ceiling. ZenMux is closer to the infrastructure layer you need when AI coding becomes a real production habit.

Fable 5 comes back！It can now build playable game prototypes. I think it is actually a signal for where AI coding is going. Making a game is not just “write some code.” Even a small browser game needs: game loop；character movement；collision logic；scoring system；UI states；physics tuning；visual feedback；bug fixing；playtesting This is why game prototyping is a great test for AI models. A model cannot fake it with a pretty answer. Either the game runs, or it does not. What impressed me about Fable 5 is that it is useful for the messy middle: turning an idea into mechanics, turning mechanics into code, debugging broken interactions, and iterating until the prototype feels playable. But here is the practical part: I would not use the strongest model for every step. For game building, I would split the workflow: 1. Fable 5 for game design + architecture 2. a fast coding model for routine implementation 3. a vision-capable model for screenshot/UI feedback 4. a cheaper model for docs, test cases, and small fixes 5. fallback when latency, cost, or output quality becomes a problem That is the real AI coding stack. Not “one magic model does everything.” More like: the right model, for the right task, at the right cost, with fallback when things break. This is why I’ve been looking at ZenMux ZenMux. ZenMux gives developers one gateway to access multiple leading AI models, with OpenAI / Anthropic / Google Vertex compatible APIs, cost tracking, quality benchmarks, auto-routing, and compensation when output quality, latency, or throughput falls short. If AI can now make games, the next question is not just “which model is strongest?” It is:how do we manage the whole model workflow Fable 5 shows the creative ceiling. ZenMux is closer to the infrastructure layer you need when AI coding becomes a real production habit.

Rachel🥥

57,766 просмотров • 17 дней назад

Claude Fable 5 + Claude Design is f*cking insane 🤯 Anthropic just dropped its most intelligent model ever, and the first thing I pointed it at was email design. I built a complete email campaign design in Claude Design, and the difference is night and day: tighter layouts, cleaner hierarchy, on-brand from the first generation. All inside Claude Design with Fable 5. Perfect for DTC brands and agencies who are still paying email agencies $3-5K/month for campaign designs that take 2 weeks to ship. If your campaign calendar is packed but every new email means briefing a designer, waiting on mockups, sending notes, and waiting again... This workflow eliminates the entire bottleneck: → Load your brand design system into Claude Design once (colors, fonts, logo, button styling) → Switch the model to Claude Fable 5 — Anthropic's new state-of-the-art model with the best vision of any AI → Prompt the campaign email section by section: header, hero, headline, offer block, CTA → Fable 5 nails layout and brand details that older models fumbled → Iterate inline — swap images, adjust styling, color-pick directly in the canvas → Export the finished email and hand off to your ESP No briefing a designer. No 2-week turnaround on a single campaign. No paying an agency $4K/month for 4 emails. What you get: → Campaign emails designed in minutes, not weeks → A reusable design system every new email pulls from automatically → Noticeably smarter design decisions from Fable 5's upgraded vision → Full inline editing before anything touches your ESP Built 100% with Claude Design + Claude Fable 5. I recorded a full walkthrough showing exactly how this works. Want it for free? > Like this post > Comment "FABLE" And I'll send it over (must be following so I can DM)

Mike Futia

42,670 просмотров • 1 месяц назад

Fable 5 just dropped and someone already built a $10k-looking website with it. Here's the full workflow The smooth scrolling, the animations, the transitions, all built with Fable 5. Here's how to get the same result instead of a generic template. 1. Steal a direction first. Go to Mobbin or Godly and find a site whose feel you love. Screenshot it. Fable copies a vibe far better than it invents one. 2. Grab real components. Pull animation-ready blocks from Aceternity UI or Magic UI. These are built for exactly this look (scroll reveals, parallax, gradients). 3. Prompt Fable with all of it. Switch to Fable 5 in Claude Code, drop in your screenshots and the component references, and describe the sections and scroll behavior you want. Let it plan before it builds. 4. Animate with the right tools. Tell it to use GSAP with ScrollTrigger for scroll effects, or Framer Motion for React. This is what separates "nice" from "$10k." 5. Iterate on feel, not code. Preview it, then give Fable specific notes ("slower fade, more spacing on mobile") until it lands. Bookmark this

Fable 5 just dropped and someone already built a $10k-looking website with it. Here's the full workflow The smooth scrolling, the animations, the transitions, all built with Fable 5. Here's how to get the same result instead of a generic template. 1. Steal a direction first. Go to Mobbin or Godly and find a site whose feel you love. Screenshot it. Fable copies a vibe far better than it invents one. 2. Grab real components. Pull animation-ready blocks from Aceternity UI or Magic UI. These are built for exactly this look (scroll reveals, parallax, gradients). 3. Prompt Fable with all of it. Switch to Fable 5 in Claude Code, drop in your screenshots and the component references, and describe the sections and scroll behavior you want. Let it plan before it builds. 4. Animate with the right tools. Tell it to use GSAP with ScrollTrigger for scroll effects, or Framer Motion for React. This is what separates "nice" from "$10k." 5. Iterate on feel, not code. Preview it, then give Fable specific notes ("slower fade, more spacing on mobile") until it lands. Bookmark this

Fokki

72,175 просмотров • 14 дней назад

Flappy Bird w/ DeepSeek V4 Pro vs GLM 5.2 vs Fable 5 I ran a small experiment: same game, same prompt, three different models. Test setup was simple: /𝚍𝚎𝚜𝚒𝚐𝚗 in Command Code. The thing I cared about was not UI. UI is now relatively easy for models to imitate. I cared more about UX: whether the model understands the interaction, the flow, the hierarchy, the little product decisions that make something feel usable. 𝙲𝚘𝚜𝚝𝚜: 𝙳𝚎𝚎𝚙𝚂𝚎𝚎𝚔 𝚟𝟺 𝙿𝚛𝚘: $𝟶.𝟶𝟶𝟶𝟾 𝙶𝙻𝙼 𝟻.𝟸: $𝟶.𝟶𝟺𝟾 𝙵𝚊𝚋𝚕𝚎 𝟻: $𝟶.𝟺𝟸 The surprising result was that Fable 5 did not produce a meaningfully better UX. It was good, but not good enough to justify the pricing delta for this kind of design task. Open-source models are getting very interesting here. They are much cheaper, competitive on UI, and increasingly good enough on UX. The gap is closing fast.

Flappy Bird w/ DeepSeek V4 Pro vs GLM 5.2 vs Fable 5 I ran a small experiment: same game, same prompt, three different models. Test setup was simple: /𝚍𝚎𝚜𝚒𝚐𝚗 in Command Code. The thing I cared about was not UI. UI is now relatively easy for models to imitate. I cared more about UX: whether the model understands the interaction, the flow, the hierarchy, the little product decisions that make something feel usable. 𝙲𝚘𝚜𝚝𝚜: 𝙳𝚎𝚎𝚙𝚂𝚎𝚎𝚔 𝚟𝟺 𝙿𝚛𝚘: $𝟶.𝟶𝟶𝟶𝟾 𝙶𝙻𝙼 𝟻.𝟸: $𝟶.𝟶𝟺𝟾 𝙵𝚊𝚋𝚕𝚎 𝟻: $𝟶.𝟺𝟸 The surprising result was that Fable 5 did not produce a meaningfully better UX. It was good, but not good enough to justify the pricing delta for this kind of design task. Open-source models are getting very interesting here. They are much cheaper, competitive on UI, and increasingly good enough on UX. The gap is closing fast.

Ahmad Awais

26,661 просмотров • 11 дней назад

BREAKING: Anthropic just dropped Opus 4.8—and it is a MONSTER We've been testing for about a week Every 📧 and our verdict is they could've just called it Opus 5, it's that good. Here's our vibe check: - Beats GPT-5.5 on Senior Engineer bench. On our toughest benchmark Opus 4.8 scores a 63—a hair higher than GPT-5.5's score of 62, and a full 30 points higher than Opus 4.7. It tackled a ground-up rewrite of a production codebase, and actually built something that works. HOWEVER: Coding performance varied a lot at different reasoning levels. We recommend using it on xhigh for best results. - Incredibly good writer. Opus 4.8 scored a 79.6 on our writing benchmark—measuring models on real-world writing tasks we do all of the time like essay writing, promo email writing, and more. It beats GPT-5.5 by 6 points. It produces well-written prose with fewer "AI-isms". It's also very good at writing in your voice given the right context. HOWEVER: Writing performance also varied with reasoning levels. Medium reasoning had higher incidence of AI-isms—we found best results with high. - Beast at knowledge work. Opus 4.8 is very good at general knowledge work tasks like report creation, research and more. It produced the best PowerPoint one-shot we've ever seen on our deck generation benchmark. - Emotionally intelligent, willing to question the frame. I've also found it to be quite good at talking through psychological or interpersonal issues. It has a high EQ, and it's also good at not glazing and helping to expand your perspective. Its thought process feels extremely rich and dynamic. THE BAD: These days a model is only as good as its harness, and Codex is still a far superior harness to the Claude Desktop app. This has kept me using Codex + GPT-5.5 as my daily driver, but I am flipping back and forth a lot more between Codex and Claude. Anthropic is back baby! Read the rest on Every 📧:

BREAKING: Anthropic just dropped Opus 4.8—and it is a MONSTER We've been testing for about a week Every 📧 and our verdict is they could've just called it Opus 5, it's that good. Here's our vibe check: - Beats GPT-5.5 on Senior Engineer bench. On our toughest benchmark Opus 4.8 scores a 63—a hair higher than GPT-5.5's score of 62, and a full 30 points higher than Opus 4.7. It tackled a ground-up rewrite of a production codebase, and actually built something that works. HOWEVER: Coding performance varied a lot at different reasoning levels. We recommend using it on xhigh for best results. - Incredibly good writer. Opus 4.8 scored a 79.6 on our writing benchmark—measuring models on real-world writing tasks we do all of the time like essay writing, promo email writing, and more. It beats GPT-5.5 by 6 points. It produces well-written prose with fewer "AI-isms". It's also very good at writing in your voice given the right context. HOWEVER: Writing performance also varied with reasoning levels. Medium reasoning had higher incidence of AI-isms—we found best results with high. - Beast at knowledge work. Opus 4.8 is very good at general knowledge work tasks like report creation, research and more. It produced the best PowerPoint one-shot we've ever seen on our deck generation benchmark. - Emotionally intelligent, willing to question the frame. I've also found it to be quite good at talking through psychological or interpersonal issues. It has a high EQ, and it's also good at not glazing and helping to expand your perspective. Its thought process feels extremely rich and dynamic. THE BAD: These days a model is only as good as its harness, and Codex is still a far superior harness to the Claude Desktop app. This has kept me using Codex + GPT-5.5 as my daily driver, but I am flipping back and forth a lot more between Codex and Claude. Anthropic is back baby! Read the rest on Every 📧:

Dan Shipper 📧

353,332 просмотров • 1 месяц назад

I can't believe this is real I have GLM 5.2 running 100% locally on my Mac Studio. 2 bit quant. The results I'm getting are better than Opus 4.8 It's now powering my Hermes Agent and Codex. 100% free, local, private super intelligence on my desk I also have it in a loop coding for me 24/7 now I thought we were at least a year away from this type of event. It happened today. The model takes up about 250gb of memory. So you can technically run it on a Mac Studio with 256gb, but you probably want the 512gb memory version (please tell me you listened to me 5 months ago when these were sitting on store shelves) With Fable gone, I now have Opus 4.8 level intelligence on my desk for free. This is the future. Local, private, secure, personal super intelligence. If you're still writing off local AI as a fad or engagement bait, you are officially delusional

I can't believe this is real I have GLM 5.2 running 100% locally on my Mac Studio. 2 bit quant. The results I'm getting are better than Opus 4.8 It's now powering my Hermes Agent and Codex. 100% free, local, private super intelligence on my desk I also have it in a loop coding for me 24/7 now I thought we were at least a year away from this type of event. It happened today. The model takes up about 250gb of memory. So you can technically run it on a Mac Studio with 256gb, but you probably want the 512gb memory version (please tell me you listened to me 5 months ago when these were sitting on store shelves) With Fable gone, I now have Opus 4.8 level intelligence on my desk for free. This is the future. Local, private, secure, personal super intelligence. If you're still writing off local AI as a fad or engagement bait, you are officially delusional

Alex Finn

618,515 просмотров • 1 месяц назад

$📢Announcing our 3D head avatar benchmark📢 Two tasks with hidden test sets: - Dynamic Novel View Synthesis on Heads - Monocular FLAME-driven Head Avatar Reconstruction Our goal is to make research on 3D head avatars more comparable and ultimately increase the realism of digital humans. The benchmark studies distinct phenomena of 3D head avatar creation, such as extreme facial expressions, slow motion captures of shaking long hair, or complicated light reflection and refraction patterns of glasses. The two benchmark tasks assess two core desiderata of 3D avatars: While the novel view synthesis challenge focuses on best possible rendering quality of complex moving scenes, the avatar animation challenge is concerned with how well a driving signal is translated into an avatar. Evaluations are light-weight and consist of diverse video recordings from the popular NeRSemble dataset with a hidden test set. Participation in the benchmark is therefore straight-forward and requires only 5 reconstructions per task. Leaderboard and benchmark submission: Benchmark data access and toolkit: Great work by Tobias Kirschstein Simon Giebenhain$

📢Announcing our 3D head avatar benchmark📢 Two tasks with hidden test sets: - Dynamic Novel View Synthesis on Heads - Monocular FLAME-driven Head Avatar Reconstruction Our goal is to make research on 3D head avatars more comparable and ultimately increase the realism of digital humans. The benchmark studies distinct phenomena of 3D head avatar creation, such as extreme facial expressions, slow motion captures of shaking long hair, or complicated light reflection and refraction patterns of glasses. The two benchmark tasks assess two core desiderata of 3D avatars: While the novel view synthesis challenge focuses on best possible rendering quality of complex moving scenes, the avatar animation challenge is concerned with how well a driving signal is translated into an avatar. Evaluations are light-weight and consist of diverse video recordings from the popular NeRSemble dataset with a hidden test set. Participation in the benchmark is therefore straight-forward and requires only 5 reconstructions per task. Leaderboard and benchmark submission: Benchmark data access and toolkit: Great work by Tobias Kirschstein Simon Giebenhain

Matthias Niessner

28,075 просмотров • 1 год назад

🚨 WARNING ANTHROPIC JUST RELEASED NEW CLAUDE FABLE 5. Most people think this is bullish. They are missing the real story. This is a Mythos-class AI model accessible for everyone. That includes: • Scammers • Exploiters • Hackers • Blackhat groups And crypto is the easiest target. The next 24 hours could get ugly: • Wallet drains • Phishing attacks • Smart contract exploits • DeFi protocol hacks Every new AI release makes attackers stronger. Assume nothing is safe. Check every link. Verify every transaction. Trust nobody. ASSUME NOTHING IS SAFE NOW. I’ve been in finance for more than 15 years. When I EXIT the markets completely, I’ll say it here publicly, like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

🚨 WARNING ANTHROPIC JUST RELEASED NEW CLAUDE FABLE 5. Most people think this is bullish. They are missing the real story. This is a Mythos-class AI model accessible for everyone. That includes: • Scammers • Exploiters • Hackers • Blackhat groups And crypto is the easiest target. The next 24 hours could get ugly: • Wallet drains • Phishing attacks • Smart contract exploits • DeFi protocol hacks Every new AI release makes attackers stronger. Assume nothing is safe. Check every link. Verify every transaction. Trust nobody. ASSUME NOTHING IS SAFE NOW. I’ve been in finance for more than 15 years. When I EXIT the markets completely, I’ll say it here publicly, like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

DANNY

27,536 просмотров • 1 месяц назад

claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.

claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.

jacob

55,515 просмотров • 1 месяц назад

Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.

Right now, you may not have access to models like GPT‑5.6 Sol, GPT‑4.6 Terra, GPT‑5.6 Luna, Claude Mythos 5, or Claude Fable 5. But you can run something surprisingly powerful today, locally, and completely free. in the next 10 mins on your 8 GB VRAM gaming laptop. Gemma 4 26B A4B QAT (MoE) delivers strong performance on a standard 8 GB VRAM GPU using Ollama, with no API, no usage limits, and no external dependencies. Out of the box, it reaches around 20 tokens per second without any optimizations. Only one command in your terminal: Ollama run gemma4:26b This means: Full offline capability (privacy by default) Zero recurring cost Competitive performance for many real world tasks Fast enough for interactive use on cheap consumer hardware If you're waiting for cutting edge cloud models, you're missing what is already practical today: a capable, local LLM that runs entirely on your own machine.

Alok

64,883 просмотров • 22 дней назад

Claude Fable 5 was too powerful, it used to watch the weather world wide, the second a season turned, it restyled a local business's storefront for it and mailed the owner the contractor who'd build it on autopilot here's how you build the same system with claude opus 4.8 + openclaw: - monitors live weather in every city in real time (free public data) - catches the season the moment it turns: rain, heat, winter - pulls a real business, its address and storefront photo from google - vision-checks the frontage, rejects the ones with no patio - renders that exact storefront for the season: rain canopy, patio heaters, shade + misting - prints the pitch on a postcard: "winter's coming, keep your patio open" - mails it to the owner, signed by the installer, with a QR to the render every step from the forecast to the render to the mailbox is automated reply "SEASON" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

Claude Fable 5 was too powerful, it used to watch the weather world wide, the second a season turned, it restyled a local business's storefront for it and mailed the owner the contractor who'd build it on autopilot here's how you build the same system with claude opus 4.8 + openclaw: - monitors live weather in every city in real time (free public data) - catches the season the moment it turns: rain, heat, winter - pulls a real business, its address and storefront photo from google - vision-checks the frontage, rejects the ones with no patio - renders that exact storefront for the season: rain canopy, patio heaters, shade + misting - prints the pitch on a postcard: "winter's coming, keep your patio open" - mails it to the owner, signed by the installer, with a QR to the render every step from the forecast to the render to the mailbox is automated reply "SEASON" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

Chris

37,397 просмотров • 1 месяц назад

let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell

let me explain what Anthropic just did they built an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tell

klöss

21,270 просмотров • 3 месяцев назад

🚨This is insane… this guy built a clawdbot that flipped $69 into $1M+ on POLYMARKET Sounds insane? 100%. Fake? Not even remotely. If you trade on Polymarket, this should have YOUR focus. A fresh wallet just surfaced with 22,173 resolved predictions and $1,013,168 in PNL It trades strictly in NEW 5-minute & 15-minute crypto markets Profile → COPYTRADE → Weekly profit is sitting around ~$100,000 And what powers it is almost offensively simple I reviewed the entire setup No sophisticated ML stacks No institutional-grade systems No complex data pipelines Just automated execution paired with statistical edge His COMPLETE playbook: 1. Ultra-short timeframes Only 5-min Up/Down contracts. Locked into 5 & 15m markets exclusively. Clawdbot-style execution framework. Pure intraday momentum extraction. No swing positions. No storytelling. Just speed and repetition 2. Order splitting + micro sizing Every position is broken into multiple small entries. Fixed predefined size per fill. Size scales only when conviction increases. This limits drawdowns and smooths the equity curve 3. Probability farming The model doesn’t hunt for moonshots. It stacks small mathematical edges. Over thousands of trades = that compounds into six figures monthly Largest trade so far: “Bitcoin Up or Down - January 19, 5-6AM ET” $13,320 → $36,887 (+176%) Now the important part: This can be replicated cursor + py-clob-client + python install the SDK generate Polymarket API keys define the Clawdbot strategy prompt AI builds the Clawdbot execution logic paper test with $1 You don’t need elite discretionary skill Bottom line Why are you still trading manually while automated systems run 24/7?

Shelpid.WI3M

10,486 просмотров • 4 месяцев назад

An OpenAI engineer stopped me at a hackathon in Hayes Valley I had my terminal open on a table. Three panels. Live trades scrolling. He was walking past and froze. "That's not a demo. That's a live scoring engine. What model is that" I told him. Claude Opus 4.7. Four repos. $25 a month. He pulled up a chair without asking. "We benchmarked Opus 4.7 internally. It beat o3 on structured reasoning across every eval we ran. And you're telling me you're using it to trade" I told him it does more than trade. It reads 86 million trades and finds who wins and why. No fine-tuning. No prompting chains. Just raw context. He leaned back. "Show me the data source" I opened one link. 86 million trades. Every wallet. Every entry. Every exit. "You point Opus 4.7 at this and it reverse-engineers the strategy. It finds the wallets that win. Then it finds why they win. Then it copies the pattern" His team spent 14 months building something similar. 10 engineers. Custom infra. Still in staging. "The part that killed us was exit timing. Every model we trained nailed entries. But the best traders exit before the crowd. We never figured out the threshold" I told him my bot cuts at 85% of expected move. Or on a 3x volume spike. Whichever comes first. He stopped talking. "How did you find that" Opus 4.7 found it in poly_data. Top wallets exit before resolution 86% of the time. Losers hold to 58%. Exits are the entire game. I opened another tab. "Three commands. 500 markets. Opus scores them in 20 minutes" "That's our internal eval pipeline. Except it took us a year and you did it in a weekend with our competitor's model" My setup: Claude Opus 4.7 - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400 in 19 days. Copytrade here: I showed him the article where I broke down every repo and every command. He read it twice. Then looked up. "You just published what we've been trying to ship for six months. Using the other team's model" He texted me the next day. "My manager found your thread. Delete it" Too late.

An OpenAI engineer stopped me at a hackathon in Hayes Valley I had my terminal open on a table. Three panels. Live trades scrolling. He was walking past and froze. "That's not a demo. That's a live scoring engine. What model is that" I told him. Claude Opus 4.7. Four repos. $25 a month. He pulled up a chair without asking. "We benchmarked Opus 4.7 internally. It beat o3 on structured reasoning across every eval we ran. And you're telling me you're using it to trade" I told him it does more than trade. It reads 86 million trades and finds who wins and why. No fine-tuning. No prompting chains. Just raw context. He leaned back. "Show me the data source" I opened one link. 86 million trades. Every wallet. Every entry. Every exit. "You point Opus 4.7 at this and it reverse-engineers the strategy. It finds the wallets that win. Then it finds why they win. Then it copies the pattern" His team spent 14 months building something similar. 10 engineers. Custom infra. Still in staging. "The part that killed us was exit timing. Every model we trained nailed entries. But the best traders exit before the crowd. We never figured out the threshold" I told him my bot cuts at 85% of expected move. Or on a 3x volume spike. Whichever comes first. He stopped talking. "How did you find that" Opus 4.7 found it in poly_data. Top wallets exit before resolution 86% of the time. Losers hold to 58%. Exits are the entire game. I opened another tab. "Three commands. 500 markets. Opus scores them in 20 minutes" "That's our internal eval pipeline. Except it took us a year and you did it in a weekend with our competitor's model" My setup: Claude Opus 4.7 - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400 in 19 days. Copytrade here: I showed him the article where I broke down every repo and every command. He read it twice. Then looked up. "You just published what we've been trying to ship for six months. Using the other team's model" He texted me the next day. "My manager found your thread. Delete it" Too late.

Lunar

136,513 просмотров • 3 месяцев назад