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This model is insane at landing pages. I asked DeepSeek V4.1 Flash & Claude Fable 5 to build me a landing page for a movie theater. Fable cost $1.21 while V4.1 Flash cost 2.6 cents, making it more than 40x cheaper at similar quality. Gave both the exact same prompt!

Hassan

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54,367 просмотров • 3 дней назад •via X (Twitter)

Искусство Образование Наука и технологии

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DeepSeek V4 Flash 0731 is now 90% off on Nous Portal for the next 7 days, in partnership with Novita AI. At this discounted price, it is over 1000x cheaper than Fable 5 on comparable tasks while still beating it on Terminal-Bench 2.1. Try it today at

DeepSeek V4 Flash 0731 is now 90% off on Nous Portal for the next 7 days, in partnership with Novita AI. At this discounted price, it is over 1000x cheaper than Fable 5 on comparable tasks while still beating it on Terminal-Bench 2.1. Try it today at

Nous Research

857,084 просмотров • 1 месяц назад

🚨Breaking: Ox Alpha is GLM 5.3 Flash by Z.ai! It's already available in Kilo, so we put it to the test. We gave the same prompt to both GLM 5.3 Flash and Gemini 3.7 Flash: Build a spectral audio visualizer. Costs: GLM 5.3 Flash: $0.01 Gemini 3.7 Flash: $0.17 17x cheaper for GLM 5.3 Flash. Who won on one-shot results?

🚨Breaking: Ox Alpha is GLM 5.3 Flash by Z.ai! It's already available in Kilo, so we put it to the test. We gave the same prompt to both GLM 5.3 Flash and Gemini 3.7 Flash: Build a spectral audio visualizer. Costs: GLM 5.3 Flash: $0.01 Gemini 3.7 Flash: $0.17 17x cheaper for GLM 5.3 Flash. Who won on one-shot results?

Kilo (acq. by Anaconda)

21,683 просмотров • 18 дней назад

Working on a new skill where Fable acts as an orchestrator and delegates work to OpenCode subagents running OSS models. It delegates to GLM 5.3 Flash for easier tasks and Kimi K3 for harder tasks, all running on Together AI. GLM 5.3 Flash is 100x cheaper than Fable for output tokens while being pretty good at coding so I'm excited to experiment with how well this works.

Working on a new skill where Fable acts as an orchestrator and delegates work to OpenCode subagents running OSS models. It delegates to GLM 5.3 Flash for easier tasks and Kimi K3 for harder tasks, all running on Together AI. GLM 5.3 Flash is 100x cheaper than Fable for output tokens while being pretty good at coding so I'm excited to experiment with how well this works.

Hassan

34,889 просмотров • 11 дней назад

GPT-6 Astra vs Fable 5.1 vs Kimi K3 vs Sol Astra: Took 11 minutes. This is from a follow-up after the first attempt had rendering and UI bugs. The smoke feels a little off. I expected more detail, but it did a good job understanding the intent. Cost: $12.85. Fable 5.1: Took 18 minutes to complete the same test with high detailing. Cost: $12.60. Kimi K3: Took 10 minutes with a similar level of output and cost only $6.95. SOL: Took 7 minutes, but the output seemed messy. Cost: $5.78. Personally, I like Kimi K3 for delivering similar quality with better token efficiency, followed by fable 5.1 for realism. What about you? I’ll do a couple more tests before coming to a conclusion.

GPT-6 Astra vs Fable 5.1 vs Kimi K3 vs Sol Astra: Took 11 minutes. This is from a follow-up after the first attempt had rendering and UI bugs. The smoke feels a little off. I expected more detail, but it did a good job understanding the intent. Cost: $12.85. Fable 5.1: Took 18 minutes to complete the same test with high detailing. Cost: $12.60. Kimi K3: Took 10 minutes with a similar level of output and cost only $6.95. SOL: Took 7 minutes, but the output seemed messy. Cost: $5.78. Personally, I like Kimi K3 for delivering similar quality with better token efficiency, followed by fable 5.1 for realism. What about you? I’ll do a couple more tests before coming to a conclusion.

Bhavy☄️

77,499 просмотров • 9 дней назад

Fable 5 totally crushed our new contest, but it cost 6x more than Opus 4.8! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: — A train derailing off a broken bridge into the water — Two cars jumping off ramps and colliding mid-air over a canyon — A monster truck crushing a row of parked cars Outputs: Fable 5: 62,158 tokens, $3.12 GPT 5.5: 37,753 tokens, $1.14 Opus 4.8: 22,280 tokens, $0.56 GLM 5.2: 36,246 tokens, $0.08 Fable 5 did all three scenes at A+. The crashes looked real, things fell and broke the right way, and nothing went through the ground or floated. GPT 5.5 was the closest to Fable. In the Bigfoot show, we think GPT was even a little better. GLM 5.2 did not win any scene, but it was the cheapest by far. Fable is the best pick for quality, but you pay more for it.

Fable 5 totally crushed our new contest, but it cost 6x more than Opus 4.8! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: — A train derailing off a broken bridge into the water — Two cars jumping off ramps and colliding mid-air over a canyon — A monster truck crushing a row of parked cars Outputs: Fable 5: 62,158 tokens, $3.12 GPT 5.5: 37,753 tokens, $1.14 Opus 4.8: 22,280 tokens, $0.56 GLM 5.2: 36,246 tokens, $0.08 Fable 5 did all three scenes at A+. The crashes looked real, things fell and broke the right way, and nothing went through the ground or floated. GPT 5.5 was the closest to Fable. In the Bigfoot show, we think GPT was even a little better. GLM 5.2 did not win any scene, but it was the cheapest by far. Fable is the best pick for quality, but you pay more for it.

atomic.chat

2,840,649 просмотров • 2 месяцев назад

I don’t think people realize how big a jump Grok 4.6 is. Look at this comparison with Fable on the same prompt. They’re pretty close, but Grok took half the time at ONE TENTH the cost. And I prefer a lot of choices Grok made: - fills the hero image to the top instead of leaving an ugly white strip - flat sharp tiles instead of the usual rounded card slop - fewer pointless labels and elements, more restraint - lighter text, less dense and overwhelming Fable certainly has more depth if you’re trying to do crazy edge-of-distribution stuff. It’s a much bigger model. But for the majority of work, you can get Fable quality for a 90% discount. Just insane how much of a step up it is from Grok 4.5.

I don’t think people realize how big a jump Grok 4.6 is. Look at this comparison with Fable on the same prompt. They’re pretty close, but Grok took half the time at ONE TENTH the cost. And I prefer a lot of choices Grok made: - fills the hero image to the top instead of leaving an ugly white strip - flat sharp tiles instead of the usual rounded card slop - fewer pointless labels and elements, more restraint - lighter text, less dense and overwhelming Fable certainly has more depth if you’re trying to do crazy edge-of-distribution stuff. It’s a much bigger model. But for the majority of work, you can get Fable quality for a 90% discount. Just insane how much of a step up it is from Grok 4.5.

Anshu

53,085 просмотров • 1 месяц назад

Claude Opus 5 just made the best Remotion video I have ever seen. Perfect transitions. Music timing locked to the frame. Branding nailed without me asking. Fable 5 held this crown for months. Opus 5 took it in one prompt. Opus 5 significantly outperforms Fable 5 at marketing videos, and it is not close. Watch this and remember Opus 5 made it.

Claude Opus 5 just made the best Remotion video I have ever seen. Perfect transitions. Music timing locked to the frame. Branding nailed without me asking. Fable 5 held this crown for months. Opus 5 took it in one prompt. Opus 5 significantly outperforms Fable 5 at marketing videos, and it is not close. Watch this and remember Opus 5 made it.

BridgeMind

188,558 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🥥

61,441 просмотров • 2 месяцев назад

holy sh*t. this is f**king insane. muse spark 1.3 beats fable 5 and gpt 5.6 at 1/20th price i cancelled my $200/mo Claude subscription for this. i replaced fable 5 with muse spark 1.3 for only $10/mo on opencode go [it takes 3 minutes to set up:] 1/ install the model-router repo 2/ toggle opencode free to green 3/ that’s it.

holy sh*t. this is f**king insane. muse spark 1.3 beats fable 5 and gpt 5.6 at 1/20th price i cancelled my $200/mo Claude subscription for this. i replaced fable 5 with muse spark 1.3 for only $10/mo on opencode go [it takes 3 minutes to set up:] 1/ install the model-router repo 2/ toggle opencode free to green 3/ that’s it.

Avid

68,916 просмотров • 10 дней назад

deepseek v4 pro is basically free right now 😳 teamorouter is offering deepseek v4 pro at almost no cost you can also use deepseek v4 flash for free what you get: - deepseek v4 pro free - deepseek v4 flash free - 1M context - openai compatible api - no subscription - credits never expire why this is worth checking: > v4 pro is currently listed at $0 input and output > flash is also available at $0 > works with claude code, codex and other tools > one api gives you access to multiple models getting started: 1. go to 2. create your account 3. open the dashboard 4. create your api key base url: 5. add it to your ai coding tool 6. select deepseek-v4-pro-free worth testing while it’s available

deepseek v4 pro is basically free right now 😳 teamorouter is offering deepseek v4 pro at almost no cost you can also use deepseek v4 flash for free what you get: - deepseek v4 pro free - deepseek v4 flash free - 1M context - openai compatible api - no subscription - credits never expire why this is worth checking: > v4 pro is currently listed at $0 input and output > flash is also available at $0 > works with claude code, codex and other tools > one api gives you access to multiple models getting started: 1. go to 2. create your account 3. open the dashboard 4. create your api key base url: 5. add it to your ai coding tool 6. select deepseek-v4-pro-free worth testing while it’s available

K2S

38,998 просмотров • 26 дней назад

Every time a new model drops, someone says designers are dead. Fable 5 is the biggest one yet. So I gave it the LottieFiles Creator MCP and asked it to animate. Real Lottie, one prompt, runs in production. Does this kill motion designers, or finally put it in everyone's hands?

Every time a new model drops, someone says designers are dead. Fable 5 is the biggest one yet. So I gave it the LottieFiles Creator MCP and asked it to animate. Real Lottie, one prompt, runs in production. Does this kill motion designers, or finally put it in everyone's hands?

Nattu

36,042 просмотров • 3 месяцев назад

GPT-6 Astra might be openai's biggest visual glow-up I gave it an ace of hearts, along with Claude Fable 5.1, Muse Spark 1.3, and Gemini 3.8 Flash. Asked them to draw an expressive eye and make sure it actually looks like a real one here's the result. look at GPT-6 Astra work.

GPT-6 Astra might be openai's biggest visual glow-up I gave it an ace of hearts, along with Claude Fable 5.1, Muse Spark 1.3, and Gemini 3.8 Flash. Asked them to draw an expressive eye and make sure it actually looks like a real one here's the result. look at GPT-6 Astra work.

Ann Nguyen

309,177 просмотров • 9 дней назад

this is literally f**king insane i just 2x my usage limits on $200/mo codex i figured out how to use deepseek v4.1-flash on $10/mo opencode go for routine subagent work... while gpt-6 astra directs the project and sol handles implementation. here's how to set it up in 3 mins: → connect opencode go to codex through model-router → install quota flow, including its skill and agent profiles → open a fresh astra task and paste: quota flow tells flash to handle discovery and checks, sol to implement, and luna to review when needed. the same implementation agent keeps its context through the build → test → fix loop. every extra agent should earn its call.

this is literally f**king insane i just 2x my usage limits on $200/mo codex i figured out how to use deepseek v4.1-flash on $10/mo opencode go for routine subagent work... while gpt-6 astra directs the project and sol handles implementation. here's how to set it up in 3 mins: → connect opencode go to codex through model-router → install quota flow, including its skill and agent profiles → open a fresh astra task and paste: quota flow tells flash to handle discovery and checks, sol to implement, and luna to review when needed. the same implementation agent keeps its context through the build → test → fix loop. every extra agent should earn its call.

Avid

57,887 просмотров • 1 день назад

50% cheaper Claude inference with just one line of code change! - Remove → model="claude-opus-4-8" - Add → model="ship-like/claude-opus-4-8" I verified the cost saving in my own terminal by invoking the same Anthropic model with the same prompt. The underlying engineering by Ship is actually interesting, and the patterns can be used in any production LLM stack. Essentially, a trained model is a frozen artifact. Every request performs the same forward-pass, whether it extracts a date or refactors a module, because the compute decision was made at training time, before the request existed. Ship makes that decision at inference time instead. After seeing a request, it searches over executions, involving single models, cascades, ensembles, or harnesses with tools, and serves the cheapest one that will match the reference model's quality. This is not a basic router, because picking a cheaper model per query doesn't ensure the cheaper model preserves the original's behavior, like output shape, tool-call patterns, and refusals. Ship measures this equivalence directly. Outputs stay distributionally indistinguishable from the reference model, not token-identical, since two calls to the same model already differ, but they are indistinguishable in capability and behavior. Of course, some requests execute cheaply and some cost Ship more than the customer pays, but the price per request is still a flat 50% off either way, so the execution-cost variance moves off the application's bill entirely. The video below depicts the cost savings and output in my real invocation, and I partnered with the team to put this together.

50% cheaper Claude inference with just one line of code change! - Remove → model="claude-opus-4-8" - Add → model="ship-like/claude-opus-4-8" I verified the cost saving in my own terminal by invoking the same Anthropic model with the same prompt. The underlying engineering by Ship is actually interesting, and the patterns can be used in any production LLM stack. Essentially, a trained model is a frozen artifact. Every request performs the same forward-pass, whether it extracts a date or refactors a module, because the compute decision was made at training time, before the request existed. Ship makes that decision at inference time instead. After seeing a request, it searches over executions, involving single models, cascades, ensembles, or harnesses with tools, and serves the cheapest one that will match the reference model's quality. This is not a basic router, because picking a cheaper model per query doesn't ensure the cheaper model preserves the original's behavior, like output shape, tool-call patterns, and refusals. Ship measures this equivalence directly. Outputs stay distributionally indistinguishable from the reference model, not token-identical, since two calls to the same model already differ, but they are indistinguishable in capability and behavior. Of course, some requests execute cheaply and some cost Ship more than the customer pays, but the price per request is still a flat 50% off either way, so the execution-cost variance moves off the application's bill entirely. The video below depicts the cost savings and output in my real invocation, and I partnered with the team to put this together.

Akshay 🚀

63,725 просмотров • 1 месяц назад

Claude DESTROYS ChatGPT for building VSL funnels. I put together the Claude VSL Prompt Vault (below) I've booked 500+ calls for clients with VSL funnels. $1M generated. These prompts are how I build every single one. The same prompts behind every VSL funnel I've built since 2023. Scripts, landing pages, offer stacks, everything. This is the closest thing to hiring a funnel strategist for free. What's inside the vault: → Custom Claude System Prompt for VSL Scripts → The 5,280-Word VSL Conversion Framework → AI Audience Research Prompt (2-Part Deep Dive) → AI Competitor Funnel Analysis Prompt → AI Hook Generator (15+ Variations by Awareness Level) → AI Proof Stacking Prompt → AI Offer Architecture Builder (2-Part Sequence) → AI Landing Page Copy Prompt → AI VSL Script Audit + Rewrite Prompt Want access to this vault? → Comment "CLAUDE" → Follow and I'll DM the vault!

Claude DESTROYS ChatGPT for building VSL funnels. I put together the Claude VSL Prompt Vault (below) I've booked 500+ calls for clients with VSL funnels. $1M generated. These prompts are how I build every single one. The same prompts behind every VSL funnel I've built since 2023. Scripts, landing pages, offer stacks, everything. This is the closest thing to hiring a funnel strategist for free. What's inside the vault: → Custom Claude System Prompt for VSL Scripts → The 5,280-Word VSL Conversion Framework → AI Audience Research Prompt (2-Part Deep Dive) → AI Competitor Funnel Analysis Prompt → AI Hook Generator (15+ Variations by Awareness Level) → AI Proof Stacking Prompt → AI Offer Architecture Builder (2-Part Sequence) → AI Landing Page Copy Prompt → AI VSL Script Audit + Rewrite Prompt Want access to this vault? → Comment "CLAUDE" → Follow and I'll DM the vault!

Lucas H

13,779 просмотров • 6 месяцев 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

43,201 просмотров • 3 месяцев назад

I gave Kimi K3 and Opus 5 the exact same prompt to build a car racing game. I expected Opus 5 to take the lead. Instead, Kimi K3 finished in ~25 min for ~$8.9, while Opus 5 took 19 min and cost $14. The biggest surprise wasn’t the speed or the price. Kimi K3 built the better game. Smoother controls, better physics, and a driving experience that felt ready from the start. Opus 5 looked cleaner visually but Kimi won where it actually mattered. Nearly half the cost and the better gameplay.

I gave Kimi K3 and Opus 5 the exact same prompt to build a car racing game. I expected Opus 5 to take the lead. Instead, Kimi K3 finished in ~25 min for ~$8.9, while Opus 5 took 19 min and cost $14. The biggest surprise wasn’t the speed or the price. Kimi K3 built the better game. Smoother controls, better physics, and a driving experience that felt ready from the start. Opus 5 looked cleaner visually but Kimi won where it actually mattered. Nearly half the cost and the better gameplay.

Aman

111,571 просмотров • 1 месяц назад

HERMES AGENT NOW RUNS CLAUDE OPUS 5. NEAR FABLE 5 INTELLIGENCE. HALF THE PRICE. SELF-VERIFIES ITS OWN WORK. AVAILABLE TODAY VIA NOUS PORTAL (20% OFF ALL MODELS). Anthropic shipped Opus 5 on July 24, 2026. same $5/$25 per million tokens as Opus 4.8. but the benchmarks tell a different story. WHAT CHANGED FROM OPUS 4.8: FrontierBench v0.1: Opus 5: 43.3%. Opus 4.8: 18.7%. 2.3x jump on the same test. ARC-AGI-3: Opus 5: 30.2%. 3x better than the next closest model. beat Fable 5 on 8 out of 13 benchmarks. at half the cost ($5/$25 vs $10/$50). same price as Opus 4.8. twice the intelligence. no reason to stay on 4.8. THE SPECS: model ID: claude-opus-5 context: 1M tokens (default and maximum) max output: 128K tokens thinking: on by default effort toggle: low / medium / high per request fast mode: $10/$50, 2.5x faster knowledge cutoff: May 2026 minimum cacheable prompt: 512 tokens (was 1,024) SELF-VERIFICATION (the biggest change): Opus 5 checks its own work automatically. Anthropic says: delete your verification prompts. "include a final verification step" now causes OVER-verification because the model already does it. for Hermes /goal tasks this is a direct upgrade. the judge checks evidence. the model also checks evidence. double layer of verification without extra tokens. EFFORT TOGGLE: low: fast, cheap, routine work. medium: balanced, daily tasks. high: full reasoning, complex problems. set per request. not a global switch. matches Hermes /reasoning command: /reasoning low (routine) /reasoning high (complex) Opus 5 effort toggle + Hermes reasoning control = precise cost management per turn. WHERE OPUS 5 FITS IN HERMES: DAILY DRIVER (replaces Opus 4.8): same price. 2.3x better benchmarks. set as your main model: Desktop app / Dashboard: Models → claude-opus-5 CHIEF OF STAFF: synthesis across multiple agents. reads Kanban, prioritizes, routes tasks. self-verification catches routing errors before they cascade. COMPLEX CODING: SOTA on agentic coding benchmarks. FrontierBench 43.3% = best public model for coding. set as coder profile model. /GOAL TASKS: self-verification + completion contracts = the model proves its work AND double-checks the proof. long-horizon goals finish correctly more often. MoA AGGREGATOR: strongest synthesis model at $5/$25. pair with GPT-5.6 and Grok 4.5 as references. Opus 5 aggregates. best quality at mid-range price. presets: max-quality: reference_models: - provider: openai-codex model: gpt-5.6-sol - provider: xai model: grok-4.5 aggregator: provider: anthropic model: claude-opus-5 COMPUTER USE: near-Fable 5 quality for browser automation. at half the token cost per session. computer_use tasks burn lots of vision tokens. Opus 5 halves that bill vs Fable 5. WHAT TO KEEP OPUS 5 AWAY FROM: cron monitoring: too expensive. use DeepSeek or no_agent mode. sub-agent grunt work: use GPT-5.6 Luna ($1/$6) or DeepSeek. auxiliary tasks: use Gemini Flash. routine web extraction: use a cheap model. Opus 5 is for the turns where quality compounds. planning, synthesis, verification, complex reasoning. budget models handle everything else. NOUS PORTAL: 20% OFF ALL MODELS Nous Portal currently runs a 20% discount on all models including Opus 5. $5/$25 official → $4/$20 through Nous Portal. the cheapest way to run Opus 5 right now. hermes setup --portal select claude-opus-5 as your model. discount applies automatically. Opus 5 replaces Opus 4.8 everywhere. same price. better at everything. no tradeoff. straight upgrade. hermes update /model claude-opus-5

YanXbt

16,744 просмотров • 1 месяц назад

Fable 5 dropping again is the biggest AI moment of the year. It’s also a usage limit trap if you don’t know what you’re doing. I just mapped out the full system to run it at 10x lower cost: - 10-80-10 framework - Model routing table - Loop engineering - Codex setup - Context memory - And every mistake that burns your limit in the first hour Don’t open Fable again until you read this.

Fable 5 dropping again is the biggest AI moment of the year. It’s also a usage limit trap if you don’t know what you’re doing. I just mapped out the full system to run it at 10x lower cost: - 10-80-10 framework - Model routing table - Loop engineering - Codex setup - Context memory - And every mistake that burns your limit in the first hour Don’t open Fable again until you read this.

CyrilXBT

33,834 просмотров • 2 месяцев 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 • 2 месяцев назад