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Fable 5 on Hyperagent is producing the most creative, ambitious work we've ever seen from our agents. They're self-improving for hours towards open-ended goals. Visual reasoning has spiked noticeably. Outputs are consistently higher quality than Opus, occasionally at lower cost. 5 of our test cases below vs. Opus 4.8... show more

Hyperagent

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Hyperagent profil fotoğrafı

Hyperagent4 ay önce

1. Visualize all asteroids in the solar system from NASA data Hyperagent ran Fable 5 to pull data and design the visual. Fable’s version included visual upgrades such as orbit traces and hover details while maintaining performance. See it:

Hyperagent profil fotoğrafı

Hyperagent4 ay önce

2. Design a site plan for a 100 acre fitness retreat Hyperagent orchestrated image gen with GPT-Image-2 and Nano Banana to bring the property to life. Fable’s version considered flow patterns, while Opus 4.8 essentially dropped boxes onto a plot. See it:

Hyperagent profil fotoğrafı

Hyperagent4 ay önce

3. Reconstruct Apollo control panels from technical PDFs Hyperagent reasoned over the diagrams and documentation to create a faithful 3D simulation. Opus 4.8’s attempt skimmed over key details.

Hyperagent profil fotoğrafı

Hyperagent4 ay önce

4. Simulate the supply chain for World Cup jersey sales based on match outcomes Fable took a global view. Opus 4.8 narrowed its scope to US only and shipped glaring visual bugs (flickering).

Hyperagent profil fotoğrafı

Hyperagent4 ay önce

5. Show the effects of solar flares on aurora Hyperagent used Fable 5 to research and design a full simulation. Opus's artifact didn't load, despite claiming to have tested the work.

Ziwen profil fotoğrafı

Ziwen4 ay önce

Looks on fire!!! I also tried the Minecraft prompts and one shot it

Lydia Hallie ✨ profil fotoğrafı

Lydia Hallie ✨4 ay önce

This looks SO good 🔥🔥

Peter Mick profil fotoğrafı

Peter Mick4 ay önce

this reconstruction really is mind blowing

Thomas Ahle profil fotoğrafı

Thomas Ahle4 ay önce

I have an app built for Opus 4.8 over two weeks. It has a lot of visual glitches. Should I start over with Fable, or ask Fable to fix it?

Beginnersblog profil fotoğrafı

Beginnersblog4 ay önce

The Apollo control panel one stopped me. Reconstructing real hardware from technical PDFs is the kind of task you'd normally hand a team for weeks. The fact that it's chewing on open-ended goals for hours and getting better is the part that's hard to wrap my head around.

Yassine Zaanouni profil fotoğrafı

Yassine Zaanouni4 ay önce

I can't believe I was able to create this with Fable

Wesley profil fotoğrafı

Wesley4 ay önce

🔥 Really impressive stuff! Fable 5 has absolutely cooked Opus on these. That Apollo panel and solar flare viz are something else.

Awa K. Penn profil fotoğrafı

Awa K. Penn4 ay önce

Fable 5 looks so realistic. Just wow

Gina Acosta profil fotoğrafı

Gina Acosta4 ay önce

This feels like the right direction for agents. Less hype, more work that actually holds up

Voight profil fotoğrafı

Voight4 ay önce

Fable, the most desired model.

Galaxyhub Labs profil fotoğrafı

Galaxyhub Labs4 ay önce

It's always important to look at the scope of all models, and Fable is undoubtedly leading the way at the moment.

Anissa profil fotoğrafı

Anissa4 ay önce

Fable 5 sounds seriously impressive

ᴍᴜʀᴘʜʏ profil fotoğrafı

ᴍᴜʀᴘʜʏ4 ay önce

Fable 5 sounds quite interesting

MisterCarrillo profil fotoğrafı

MisterCarrillo4 ay önce

Everyone is comparing models. The real comparison is: What can an agent accomplish after 3 hours of autonomous work? That's where things get interesting.

Shahid Wani profil fotoğrafı

Shahid Wani4 ay önce

Woww fable 5 sound 😱

Aaliya profil fotoğrafı

Aaliya4 ay önce

The use cases are creative and interesting.

Carl downey profil fotoğrafı

Carl downey4 ay önce

good

Ryker Stone profil fotoğrafı

Ryker Stone4 ay önce

"This is bigger than most people realize. The real story isn't the ban — it's that one government just showed every other government exactly how to do it."

Shiro profil fotoğrafı

Shiro4 ay önce

İ think claude is becoming a overrated

The Operator | AI Ops for Creators profil fotoğrafı

The Operator | AI Ops for Creators4 ay önce

All the Fable demos are all fancy UI / 3D generations. Is this a 3D Artist model or an LLM

K!A🚀 profil fotoğrafı

K!A🚀4 ay önce

Fable feels less like a model, more like a working session.

Snow profil fotoğrafı

Snow4 ay önce

this is superb

mirajul profil fotoğrafı

mirajul4 ay önce

🤖 AI & ChatGPT Guides

TOny-fishkiller profil fotoğrafı

TOny-fishkiller4 ay önce

that's amazing！

Michael Suede profil fotoğrafı

Michael Suede4 ay önce

wow nice

ZLH profil fotoğrafı

ZLH4 ay önce

Amazing

Aditya Rana profil fotoğrafı

Aditya Rana4 ay önce

Looks super cool , there is no way it created it in those single line prompts through .

Ori Torii profil fotoğrafı

Ori Torii4 ay önce

Amazing! How about building websites? Any examples?

SparkTwo⚡️ はると⚡️17歳のAI自動化屋 profil fotoğrafı

SparkTwo⚡️ はると⚡️17歳のAI自動化屋4 ay önce

Claude APIで自動化パイプライン組んでいて、Fable 5に切り替えてから複数ステップの処理精度が体感30～40%上がった。Opus比でコスト下がって品質上がるのは設計の選択肢が広がる

Al-Shamus profil fotoğrafı

Al-Shamus4 ay önce

This looks impressive

Teknikforce profil fotoğrafı

Teknikforce2 ay önce

The biggest win isn't just having a better AI assistant. It's reducing the friction between thinking and doing. The same applies to content creation. Instead of spending hours editing product videos, tools like Vidicom can turn a product page into ready to publish marketing videos for YouTube, TikTok, Instagram, and more.

Shubham Sharma | AI & Tech profil fotoğrafı

Shubham Sharma | AI & Tech4 ay önce

All the Fable demos are all fancy UI / 3D generations. Is this a 3D Artist model or an LLM

Faizan Shah profil fotoğrafı

Faizan Shah4 ay önce

AI tools hallucinate. Confidently. Every day. Verity automatically fact-checks AI responses with cited web sources. Free Chrome extension 👇 #AI #ChatGPT #Claude #ChromeExtension

Benzer Videolar

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

18,509 görüntüleme • 1 ay önce

Anthropic Head of Product: "Fable 5 is the best model we've ever shipped for agentic work. Our engineers now ship 8x more code than they did in past years." in 42 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5: managed agents, dreaming, dynamic workflows worth more than a $500 agent building course live from Anthropic's latest stage in Japan, just hours ago i turned everything they showed on stage into a step-by-step guide on building your own agent you can find the full guide below

Anthropic Head of Product: "Fable 5 is the best model we've ever shipped for agentic work. Our engineers now ship 8x more code than they did in past years." in 42 minutes, the Anthropic team shows how to build self-improving agent systems with Fable 5: managed agents, dreaming, dynamic workflows worth more than a $500 agent building course live from Anthropic's latest stage in Japan, just hours ago i turned everything they showed on stage into a step-by-step guide on building your own agent you can find the full guide below

Anatoli Kopadze

81,094 görüntüleme • 4 ay önce

i gave the exact same prompt to Opus 5 and Fable 5 and here's what came out Opus 5 dropped yesterday and my feed was instantly full of comparison posts but i wanted to check it myself so i gave it one task build 3d Flappy Bird first thing everyone was saying Opus is 2x cheaper than Fable BUT.. building the game on Max effort cost me 250k tokens and 1 hour on Opus and 130k on Fable but Fable did it in half the time Opus gave me volume control plus 3 separate graphics presets to choose from, Fable gave none of that in Opus the environment shifts dynamically as you play in Fable it's basically the same frame the whole run maybe a day/night change here and there graphics, animations, glow, all of it goes to Opus and now that limits jumped 50% for the near future while Fable went paid for me the call is obvious right now Opus same prompt start to finish zero changes to code or commands want it? i can send it over

i gave the exact same prompt to Opus 5 and Fable 5 and here's what came out Opus 5 dropped yesterday and my feed was instantly full of comparison posts but i wanted to check it myself so i gave it one task build 3d Flappy Bird first thing everyone was saying Opus is 2x cheaper than Fable BUT.. building the game on Max effort cost me 250k tokens and 1 hour on Opus and 130k on Fable but Fable did it in half the time Opus gave me volume control plus 3 separate graphics presets to choose from, Fable gave none of that in Opus the environment shifts dynamically as you play in Fable it's basically the same frame the whole run maybe a day/night change here and there graphics, animations, glow, all of it goes to Opus and now that limits jumped 50% for the near future while Fable went paid for me the call is obvious right now Opus same prompt start to finish zero changes to code or commands want it? i can send it over

savip.

45,764 görüntüleme • 2 ay önce

Opus 5 is a modest upgrade, but it has tough competition in GPT-5.6 Sol Initial thoughts from our early access: > Clearer writing than Fable's dense communication style > Still gets too verbose compared to GPT models (even when explicitly instructed to keep text purposeful) > Strong on browser use inside Hyperagent > Strong on reviewing complex data to justify a decision > Less likely to take creative risks. More of a "rule follower" personality. Costs shown for five test cases (GPT-5.6 Sol was consistently much cheaper) Explore and judge the actual work for yourself in thread 👇

Opus 5 is a modest upgrade, but it has tough competition in GPT-5.6 Sol Initial thoughts from our early access: > Clearer writing than Fable's dense communication style > Still gets too verbose compared to GPT models (even when explicitly instructed to keep text purposeful) > Strong on browser use inside Hyperagent > Strong on reviewing complex data to justify a decision > Less likely to take creative risks. More of a "rule follower" personality. Costs shown for five test cases (GPT-5.6 Sol was consistently much cheaper) Explore and judge the actual work for yourself in thread 👇

Hyperagent

154,784 görüntüleme • 2 ay önce

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?

JJ Englert

10,737 görüntüleme • 3 ay önce

We’re Scaled Cognition, developing the first ever models trained specifically for agentic applications: 1. Our first system, APT-1, is now #1 on agentic benchmarks. 2. It was developed by a US team for a total cost of less than $11M. 3. Khosla Ventures led our seed round ($21M closed in 2023), and Vinod Khosla joined our board. 4. We use a fully synthetic, RL-based agentic data pipeline, no human-labeled data. 5. APT-1 is now available for early access.

We’re Scaled Cognition, developing the first ever models trained specifically for agentic applications: 1. Our first system, APT-1, is now #1 on agentic benchmarks. 2. It was developed by a US team for a total cost of less than $11M. 3. Khosla Ventures led our seed round ($21M closed in 2023), and Vinod Khosla joined our board. 4. We use a fully synthetic, RL-based agentic data pipeline, no human-labeled data. 5. APT-1 is now available for early access.

Scaled Cognition

94,548 görüntüleme • 1 yıl önce

Claude Fable 5 makes new things possible. I one shot a full horror game with it. One prompt. I have never seen AI output a game like this. This is the leap I've been waiting for. 80.3 on SWE-Bench Pro vs Opus 4.8 at 69.2, the biggest jump I have ever seen on that benchmark. It passed GPT 5.5 in both coding and intelligence on Artificial Analysis. I already canceled my $200 ChatGPT Pro plan. It fixed a Bridge Voice bug in one shot that GPT 5.5, Opus 4.7, and Opus 4.8 all failed to crack for 2 months. 10/10. Best model I have ever used. Full review below.

Claude Fable 5 makes new things possible. I one shot a full horror game with it. One prompt. I have never seen AI output a game like this. This is the leap I've been waiting for. 80.3 on SWE-Bench Pro vs Opus 4.8 at 69.2, the biggest jump I have ever seen on that benchmark. It passed GPT 5.5 in both coding and intelligence on Artificial Analysis. I already canceled my $200 ChatGPT Pro plan. It fixed a Bridge Voice bug in one shot that GPT 5.5, Opus 4.7, and Opus 4.8 all failed to crack for 2 months. 10/10. Best model I have ever used. Full review below.

BridgeMind

19,020 görüntüleme • 4 ay önce

ANTHROPIC LEAKED 6 RULES THAT RUN 8 LOOPS AT ONCE - AND ONE ENGINEER DOES THE WORK OF A TEAM one engineer with this system replaces an entire team - and costs the company 8 times less You → Opus 5 plan → Fable 5 ×8 execute → Fable 5 review → you: 5 min Opus 5 takes your intent and breaks it into subtasks - a bad plan multiplied across every loop gives the same number of disasters - the plan is the only thing you read carefully one repo - isolated worktrees for each loop - nobody stands on anyone's file - parallel PRs ship while you do nothing the agent runs the tests and fixes until green PR - a red build never reaches your eyes one CLAUDE.md for the whole fleet - without it you get different opinions from every loop and one merge hell the average engineer closes 3-4 tasks a day - this system closes a full sprint overnight with zero working hours Fable 5 pre-reviews every PR before it reaches you - you spend 5 minutes - your throughput is now measured in diffs read per hour bookmark and paste into Claude Code - your first fleet can start tonight

ANTHROPIC LEAKED 6 RULES THAT RUN 8 LOOPS AT ONCE - AND ONE ENGINEER DOES THE WORK OF A TEAM one engineer with this system replaces an entire team - and costs the company 8 times less You → Opus 5 plan → Fable 5 ×8 execute → Fable 5 review → you: 5 min Opus 5 takes your intent and breaks it into subtasks - a bad plan multiplied across every loop gives the same number of disasters - the plan is the only thing you read carefully one repo - isolated worktrees for each loop - nobody stands on anyone's file - parallel PRs ship while you do nothing the agent runs the tests and fixes until green PR - a red build never reaches your eyes one CLAUDE.md for the whole fleet - without it you get different opinions from every loop and one merge hell the average engineer closes 3-4 tasks a day - this system closes a full sprint overnight with zero working hours Fable 5 pre-reviews every PR before it reaches you - you spend 5 minutes - your throughput is now measured in diffs read per hour bookmark and paste into Claude Code - your first fleet can start tonight

Sprytix

37,904 görüntüleme • 2 ay önce

A security guard turned $900 into $187,000 on Polymarket. Guarded empty buildings for 10 years at $16/hour. One sleepless shift he built a BTC bot with Claude Opus 4.8. Never wrote a single line of code. I found his wallet. Reverse-engineered the entire system. Here is what he actually did. Gave Claude new Fable 5 two prompts at the start of his shift. Opus did not write the bot. It drew the blueprint: data, signals, backtest, risk, execution. Then handed that blueprint to a swarm of 300 agents. How it works: → Decompose: Claude Fable 5 breaks the goal into a task tree → Dispatch: 300 agents fan out (some pulling Binance data, some writing code, some backtesting 5 years of data) → Execute: 4,000 steps in one 14-hour run → Review: Claude Fable 5 reads it all back and kills whatever drifted The brain never wrote a line. The hands never made a call. By sunrise he had what a 6-engineer quant team ships in a quarter. A live BTC bot on Polymarket. Backtested. Risk-capped. Running 24/7. For 10 years he watched empty buildings. Now 300 agents watch the market while he sleeps. I rebuilt this exact system with Claude new Fable 5 You only need Claude + device + 1 hour to deploy. Giving this free for 24 hours. To get it: 1. Comment "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

A security guard turned $900 into $187,000 on Polymarket. Guarded empty buildings for 10 years at $16/hour. One sleepless shift he built a BTC bot with Claude Opus 4.8. Never wrote a single line of code. I found his wallet. Reverse-engineered the entire system. Here is what he actually did. Gave Claude new Fable 5 two prompts at the start of his shift. Opus did not write the bot. It drew the blueprint: data, signals, backtest, risk, execution. Then handed that blueprint to a swarm of 300 agents. How it works: → Decompose: Claude Fable 5 breaks the goal into a task tree → Dispatch: 300 agents fan out (some pulling Binance data, some writing code, some backtesting 5 years of data) → Execute: 4,000 steps in one 14-hour run → Review: Claude Fable 5 reads it all back and kills whatever drifted The brain never wrote a line. The hands never made a call. By sunrise he had what a 6-engineer quant team ships in a quarter. A live BTC bot on Polymarket. Backtested. Risk-capped. Running 24/7. For 10 years he watched empty buildings. Now 300 agents watch the market while he sleeps. I rebuilt this exact system with Claude new Fable 5 You only need Claude + device + 1 hour to deploy. Giving this free for 24 hours. To get it: 1. Comment "Claude" 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you

Himanshu Kumar

55,010 görüntüleme • 4 ay önce

We’re open sourcing the first document OCR benchmark for the agentic era, ParseBench. Document parsing is the foundation of every AI agent that works with real-world files. ParseBench is a benchmark that measures parsing quality specifically for agent knowledge work: ✅ It optimizes for semantic correctness (instead of exact similarity) ✅ It has the most comprehensive distribution of real-world enterprise documents It contains ~2,000 human-verified enterprise document pages with 167,000+ test rules across five dimensions that matter most: tables, charts, content faithfulness, semantic formatting, and visual grounding. We benchmarked 14 known document parsers on ParseBench, from frontier/OSS VLMs to specialized parsers to LlamaParse. Here are some of our findings: 💡 Increasing compute budget yields diminishing returns - Gemini/gpt-5-mini/haiku gain 3-5 points from minimal to high thinking, at 4x the cost. 💡 Charts are the most polarizing dimension for evaluation. Most specialized parsers score below 6%, while some VLM-based parsers do a bit better. 💡 VLMs are great at visual understanding but terrible at layout extraction. GPT-5-mini/haiku score below 10% on our visual grounding task, all specialized parsers do much better. 💡 No method crushes all 5 dimensions at once, but LlamaParse achieves the highest overall score at 84.9%, and is the leader in 4 out of the 5 dimensions. This is by far the deepest technical work that we’ve published as a company. I would encourage you to start with our blog and explore our links to Hugging Face to GitHub. All the details are in our full 35-page (!!) ArXiv whitepaper. 🌐: Blog: 📄 Paper: 💻 Code: 📊 Dataset: 🎥 YouTube:

We’re open sourcing the first document OCR benchmark for the agentic era, ParseBench. Document parsing is the foundation of every AI agent that works with real-world files. ParseBench is a benchmark that measures parsing quality specifically for agent knowledge work: ✅ It optimizes for semantic correctness (instead of exact similarity) ✅ It has the most comprehensive distribution of real-world enterprise documents It contains ~2,000 human-verified enterprise document pages with 167,000+ test rules across five dimensions that matter most: tables, charts, content faithfulness, semantic formatting, and visual grounding. We benchmarked 14 known document parsers on ParseBench, from frontier/OSS VLMs to specialized parsers to LlamaParse. Here are some of our findings: 💡 Increasing compute budget yields diminishing returns - Gemini/gpt-5-mini/haiku gain 3-5 points from minimal to high thinking, at 4x the cost. 💡 Charts are the most polarizing dimension for evaluation. Most specialized parsers score below 6%, while some VLM-based parsers do a bit better. 💡 VLMs are great at visual understanding but terrible at layout extraction. GPT-5-mini/haiku score below 10% on our visual grounding task, all specialized parsers do much better. 💡 No method crushes all 5 dimensions at once, but LlamaParse achieves the highest overall score at 84.9%, and is the leader in 4 out of the 5 dimensions. This is by far the deepest technical work that we’ve published as a company. I would encourage you to start with our blog and explore our links to Hugging Face to GitHub. All the details are in our full 35-page (!!) ArXiv whitepaper. 🌐: Blog: 📄 Paper: 💻 Code: 📊 Dataset: 🎥 YouTube:

Jerry Liu

108,403 görüntüleme • 6 ay önce

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.

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 görüntüleme • 2 ay önce

this is certified f*cking gold for anyone paying for Claude Sonnet 5.5 costs half of what Opus 5.5 does on real office work across 44 jobs it scores 1844. Opus scores 1846 on coding it went from 10.3% to 70.6% in one version and passed Opus on the way most of what you pay Opus for, Sonnet 5.5 now does at half the price here's how to split the work: • give it to Sonnet 5.5 > bug fixes and well-scoped coding tasks > decks built from your own slide template > spreadsheets and polished documents > UI polish, it has a real eye for design > fast back-and-forth, it runs 30%+ faster • keep it for Opus 5.5 > long, open-ended work with judgment calls for hours > anything where one wrong assumption costs you a day • the setting that saves the most > Medium is the default in the Claude apps and Claude Code > on Low or Medium it beats Sonnet 5's best score for a tenth of the cost > raise effort only when the first answer falls short • the price > $2 in and $10 out, against $4 and $20 for Opus > cache reads $0.20 on both • check before you switch > if you ran Sonnet with thinking off, move to the new between_tools setting first whoever routes the weekly grunt work to Sonnet 5.5 and saves Opus for the hard calls ships more on half the budget, and that's the person who gets noticed

this is certified f*cking gold for anyone paying for Claude Sonnet 5.5 costs half of what Opus 5.5 does on real office work across 44 jobs it scores 1844. Opus scores 1846 on coding it went from 10.3% to 70.6% in one version and passed Opus on the way most of what you pay Opus for, Sonnet 5.5 now does at half the price here's how to split the work: • give it to Sonnet 5.5 > bug fixes and well-scoped coding tasks > decks built from your own slide template > spreadsheets and polished documents > UI polish, it has a real eye for design > fast back-and-forth, it runs 30%+ faster • keep it for Opus 5.5 > long, open-ended work with judgment calls for hours > anything where one wrong assumption costs you a day • the setting that saves the most > Medium is the default in the Claude apps and Claude Code > on Low or Medium it beats Sonnet 5's best score for a tenth of the cost > raise effort only when the first answer falls short • the price > $2 in and $10 out, against $4 and $20 for Opus > cache reads $0.20 on both • check before you switch > if you ran Sonnet with thinking off, move to the new between_tools setting first whoever routes the weekly grunt work to Sonnet 5.5 and saves Opus for the hard calls ships more on half the budget, and that's the person who gets noticed

Annatar.md

19,642 görüntüleme • 20 gün önce

hy3 vs fable 5 vs opus 4.8 vs sonnet 5 Tencent Hy just dropped hy3 – their new open-weight model under apache 2.0. following the april preview they scaled up post-training, and it now rivals flagship open models with 2-5x the params. api pricing: ~$0.15 in / ~$0.59 out per 1m tokens. built for coding, office work, frontend, agentic tasks so we ran a test: hy3 vs fable 5 vs opus 4.8 vs sonnet 5 three prompts, one-shot each: • ocean wave crumbling a sand castle (canvas) • looping factory assembly line (html/css/js) • interactive 3d city with three.js + orbitcontrols self-contained files, no libraries beyond the cdn where asked totals across all three prompts: 1. hy3 – 1231 loc / 14m34s 2. sonnet 5 – 1373 loc / 18m55s 3. fable 5 – 1546 loc / 18m32s 4. opus 4.8 – 1904 loc / 27m21s hy3 is the fastest and the leanest by a wide margin we had opus 4.8 analyze hy3's code. the read: - sand castle: checklist-complete but the crumble is parametric, not physical. it shrinks and slumps the towers and fades alpha instead of dissolving into grains. the cheap-but-plausible interpretation. the tell of a smaller model - factory line: the arm-to-part sync is actually causal, not faked. it triggers each robot early by exactly the arm's descent time, so the tap lands right as the part arrives. it also pre-seeds the belt so it never cold-starts empty. clean state machine. one latent bug – a part gets marked processed before checking if the robot is free, so at a faster spawn rate a "laptop" could ship missing a part. never fires at current timing, but the invariant isn't enforced - 3d city: genuinely frontier-adjacent. correct modern setup (pcfsoft shadows, srgb, aces tone mapping, damped orbit + auto-rotate pause). clones the window texture per building and scales the uv repeat to each building's dimensions so windows don't stretch. downside: no instancing – ~800 texture clones across 200 buildings. runs fine, not optimized. roads are implicit gaps, not explicit planes our observations: • hy3 is quite fast • its animations are simple but you can see it trying – it adds detail, and the 3d render sits at the same level as the frontier models • sonnet 5 is weak here. hy3 beats it on the sand castle and the 3d render, level on the conveyor • opus 4.8 is anthropic's best model after the fable 5 nerf – it beats fable on the conveyor and the 3d render net: hy3 runs clean and well-formed across all three with zero syntax errors, even version-matching the three.js core and examples build. it's economical rather than ambitious – it does the minimum viable version of each hard requirement well, and only reaches for the expensive interpretation on the 3d task a very coherent profile for a cost-optimized open-weight model follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

34,961 görüntüleme • 3 ay önce

It’s #SunDay! Here’s your space weather report for the week of June 5 - 11: • 1 M-class flare • 5 C-class flares • 36 coronal mass ejections • 1 geomagnetic storm (as of June 12, though another one is currently forecast for June 13) This video from NASA’s Solar Dynamics Observatory shows the week’s activity. This week’s most powerful flare was an M1.8 on June 6, which erupts from the southeastern (lower left) region of the Sun’s disk at about 0:42 in this video. That eruption also produced a coronal mass ejection that reached Earth three days later, but the bulk of the blast was oriented to the south and east of Earth, so the effect on our planet was minimal. Learn more about solar flares and coronal mass ejections:

It’s #SunDay! Here’s your space weather report for the week of June 5 - 11: • 1 M-class flare • 5 C-class flares • 36 coronal mass ejections • 1 geomagnetic storm (as of June 12, though another one is currently forecast for June 13) This video from NASA’s Solar Dynamics Observatory shows the week’s activity. This week’s most powerful flare was an M1.8 on June 6, which erupts from the southeastern (lower left) region of the Sun’s disk at about 0:42 in this video. That eruption also produced a coronal mass ejection that reached Earth three days later, but the bulk of the blast was oriented to the south and east of Earth, so the effect on our planet was minimal. Learn more about solar flares and coronal mass ejections:

NASA Space Alerts

48,131 görüntüleme • 4 ay önce

ANTHROPIC MAPPED OUT 8 LEVELS OF AI AGENTS - AND ANYONE CAN REACH LEVEL 8 WHERE THE SYSTEM EARNS $70K WITHOUT YOU anyone can reach level 8 - one solo developer with the right architecture gets there in a few weeks level 1 - the agent can do one action - and 80% of developers call this a product level 3 - 50 tools in context at once - the model gets confused - most teams get stuck here and lose $30K/month level 4 - Opus 5 grades its own output and rejects before you see it - the first level where quality stops depending on luck level 5 - Opus 5 plans, Fable 5 executes in parallel - one brain, many hands level 7 - while you slept the agent did $3,000 worth of work and sent the report before you woke up level 8 - the fleet finds its own mistakes, patches the graph and tomorrow it is smarter than today bookmark and read below - 8 steps from level 1 to $70K/month without you

ANTHROPIC MAPPED OUT 8 LEVELS OF AI AGENTS - AND ANYONE CAN REACH LEVEL 8 WHERE THE SYSTEM EARNS $70K WITHOUT YOU anyone can reach level 8 - one solo developer with the right architecture gets there in a few weeks level 1 - the agent can do one action - and 80% of developers call this a product level 3 - 50 tools in context at once - the model gets confused - most teams get stuck here and lose $30K/month level 4 - Opus 5 grades its own output and rejects before you see it - the first level where quality stops depending on luck level 5 - Opus 5 plans, Fable 5 executes in parallel - one brain, many hands level 7 - while you slept the agent did $3,000 worth of work and sent the report before you woke up level 8 - the fleet finds its own mistakes, patches the graph and tomorrow it is smarter than today bookmark and read below - 8 steps from level 1 to $70K/month without you

Noisy

12,499 görüntüleme • 2 ay önce

Anthropic engineer: “80% of our engineers are using Loops. Now everyone is exploring how to build right Context for agents.” in 3-6 months, we’ll all become context engineers. Context is the most important part of agents.” in this 1-hour talk, Anthropic engineer shows how to build a self-improving agents from sratch. It’s worth more than a $500 agentic course. Watch this video, then read the article below on how to become a context architect.

Anthropic engineer: “80% of our engineers are using Loops. Now everyone is exploring how to build right Context for agents.” in 3-6 months, we’ll all become context engineers. Context is the most important part of agents.” in this 1-hour talk, Anthropic engineer shows how to build a self-improving agents from sratch. It’s worth more than a $500 agentic course. Watch this video, then read the article below on how to become a context architect.

Codez

36,334 görüntüleme • 2 ay önce

Jev + Opus 5.5: Anthropic's new model beats GPT-6 Astra for 1/5 the cost, and 4 API changes will 400 your agent before it writes a single line I pulled these 10 steps from the migration docs so you don't learn them in production step 1 → $4 / $20 per 1M. Opus 5 was $5 / $25. cache reads dropped from $0.50 to $0.20 step 2 → 66.4% on Terminal-Bench 4.0 vs GPT-6 Astra 57.9% and Opus 5 52.3%. +14.1 points in one release, and on FrontierCode it beats Astra at default effort for 1/5 the cost step 3 → thinking can't be turned off anymore. send thinking: disabled and you get a 400. drop the field, set effort step 4 → tool_choice any and tool are gone. 400. switch to auto + strict step 5 → edit anything above a thinking block and the request dies. append only, or opt into drop_block step 6 → computer_20251124 is dead on the API. 400. move to computer_toolset_20260801 step 7 → the quiet one: default effort fell from high to medium. your agent thinks less than you set it up to and nothing tells you step 8 → hop Opus 5.5 → Sonnet 5 → Opus 5.5 and you pay 4.36 instead of 3.32. +31%, the cache dies and Sonnet can't read Opus's reasoning step 9 → change effort at the top of the request and the cache is gone. Jev sets it per message and the cache stays step 10 → switch fast - standard mid-session and it's a full cache miss. Jev picks speed once, on turn one one model, three knobs, zero 400s. that is Jev + Opus 5.5 send this to your Claude Code before you touch the model ID, then read my full Jev deep dive in the article below ↓

Jev + Opus 5.5: Anthropic's new model beats GPT-6 Astra for 1/5 the cost, and 4 API changes will 400 your agent before it writes a single line I pulled these 10 steps from the migration docs so you don't learn them in production step 1 → $4 / $20 per 1M. Opus 5 was $5 / $25. cache reads dropped from $0.50 to $0.20 step 2 → 66.4% on Terminal-Bench 4.0 vs GPT-6 Astra 57.9% and Opus 5 52.3%. +14.1 points in one release, and on FrontierCode it beats Astra at default effort for 1/5 the cost step 3 → thinking can't be turned off anymore. send thinking: disabled and you get a 400. drop the field, set effort step 4 → tool_choice any and tool are gone. 400. switch to auto + strict step 5 → edit anything above a thinking block and the request dies. append only, or opt into drop_block step 6 → computer_20251124 is dead on the API. 400. move to computer_toolset_20260801 step 7 → the quiet one: default effort fell from high to medium. your agent thinks less than you set it up to and nothing tells you step 8 → hop Opus 5.5 → Sonnet 5 → Opus 5.5 and you pay 4.36 instead of 3.32. +31%, the cache dies and Sonnet can't read Opus's reasoning step 9 → change effort at the top of the request and the cache is gone. Jev sets it per message and the cache stays step 10 → switch fast - standard mid-session and it's a full cache miss. Jev picks speed once, on turn one one model, three knobs, zero 400s. that is Jev + Opus 5.5 send this to your Claude Code before you touch the model ID, then read my full Jev deep dive in the article below ↓

Carnage

16,674 görüntüleme • 26 gün önce

The real cost of Factory getting involved with the playbook crowd is higher than a few mean tweets. The video outlines how things might look from their perspective: 1. Tell the founder their team is horrible and the company will fail. 2. Ask them to fire their sales leader as a condition of providing your service. 3. Insist on getting paid in equity because "we are not cheap." 4. Fire most of the team and hire only playbook sales reps and protégés from before. 5. Get paid in cash for all the recruiting work. 6. Ignore and block anyone else on the board who has opinions on GTM to keep control of the narrative. Months after Factory brought them in, key advisors are now working with its largest competitor. Is it that surprising that the leadership team at Factory responded as they did? Video credit: 20VC

The real cost of Factory getting involved with the playbook crowd is higher than a few mean tweets. The video outlines how things might look from their perspective: 1. Tell the founder their team is horrible and the company will fail. 2. Ask them to fire their sales leader as a condition of providing your service. 3. Insist on getting paid in equity because "we are not cheap." 4. Fire most of the team and hire only playbook sales reps and protégés from before. 5. Get paid in cash for all the recruiting work. 6. Ignore and block anyone else on the board who has opinions on GTM to keep control of the narrative. Months after Factory brought them in, key advisors are now working with its largest competitor. Is it that surprising that the leadership team at Factory responded as they did? Video credit: 20VC

The Deal Director

48,000 görüntüleme • 14 gün önce

Anthropic engineer: “80% of our engineers are using self-improving loops. Now everyone is exploring how to build the right Context for agents.” in 3-6 months, we’ll all become context engineers. Context is the most important part of building agents.” In this 40-minute lecture, an Anthropic engineer shows how to build a self-improving agentic workflow from scratch. It’s worth more than a $500 agentic course. Watch this video, then read the article below on how to become a context architect.

Anthropic engineer: “80% of our engineers are using self-improving loops. Now everyone is exploring how to build the right Context for agents.” in 3-6 months, we’ll all become context engineers. Context is the most important part of building agents.” In this 40-minute lecture, an Anthropic engineer shows how to build a self-improving agentic workflow from scratch. It’s worth more than a $500 agentic course. Watch this video, then read the article below on how to become a context architect.

Movez

21,262 görüntüleme • 2 ay önce