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

thehype.

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14,518 次观看 • 2 个月前 •via X (Twitter)

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Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.

Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.

Dan McAteer

191,618 次观看 • 2 个月前

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 次观看 • 2 个月前

Comparisons of Sonnet 4.5 vs GPT-5 Pro. I appreciate the comparison is not exactly fair, but I've had GPT-5 Pro videos ready to go, so forgive me. Saying that it does give a good benchmark, I don't think there was a single instance of Sonnet 4.5 being better, and I was testing it in Claude Code, so it should have had an advantage of not being stuck in the web client. It doesn't mean to say that Claude 4.5 would be worse on all dimensions, these are 1-shot single file HTML files, so not going to test the full agentic suite of capabilities. Song via Suno v5 Lyrics by Sonnet 4.5

Comparisons of Sonnet 4.5 vs GPT-5 Pro. I appreciate the comparison is not exactly fair, but I've had GPT-5 Pro videos ready to go, so forgive me. Saying that it does give a good benchmark, I don't think there was a single instance of Sonnet 4.5 being better, and I was testing it in Claude Code, so it should have had an advantage of not being stuck in the web client. It doesn't mean to say that Claude 4.5 would be worse on all dimensions, these are 1-shot single file HTML files, so not going to test the full agentic suite of capabilities. Song via Suno v5 Lyrics by Sonnet 4.5

Peter Gostev (SF 24-28 August)

255,966 次观看 • 11 个月前

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.

Dan McAteer

910,847 次观看 • 3 个月前

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 次观看 • 16 天前

FREE Fable 5, Opus 4.8, Sonnet 5, and GPT-5.6 in one IDE. Alibaba built it, 520 credits at signup - one Sonnet 5 message eats 4. It's called Accio. Web or Windows desktop, both free. Registration takes 30 seconds via Google or email. Inside: → Fable 5 for creative and long-context work. → Opus 4.6 through 4.8 - the full Anthropic frontier lineup. → Sonnet 5 for speed and reasoning at pennies per message. → GPT-5.5 for OpenAI native tasks. → Gemini 3.1 Pro and 3.5 Flash for multimodal. Real math: 520 credits divided by 4 = 130 Sonnet 5 messages in your first week. Cheaper models drop that even further. Anthropic charges $20/month for the same access with weekly limits. Custom MCP support built in. Profile > Settings > MCP. Every agent workflow you've built for Claude Desktop ports over instantly. Setup: → Go to accio(.)com → Sign up with Google → 520 credits land automatically → Pick your model and start firing prompts Bookmark this before Alibaba puts it behind a paywall.

Atenov int.

31,157 次观看 • 2 个月前

ANTHROPIC LEAKED A 6-LOOP SETUP THAT REPLACES A $3,000 AGENCY AND COSTS $59 A MONTH Microsoft and Google have been running this for a while - the gap against an agency is exactly 51x. an agency charged you for waiting, not for work - the brief walked from the strategist to the copywriter to the designer for weeks. here all 6 loops read one file on the same pass - there's nobody to wait on, and the calendar is empty. 51% of the bill is production on Sonnet 5, and only 5% is strategy on Opus 5 - the priciest model runs once a week. 22% of the whole bill sits on the batch queue at half rate - where nobody is waiting for an answer right now. the journal is the only loop that writes back into the root - which angle is dead, and next week starts tighter. the 6 loops bring you 3 angles a week - the final pick stays yours, and that's the part that never automates. save this and paste it into Claude Code - the loops remove the waiting, not the judgement ↓

ANTHROPIC LEAKED A 6-LOOP SETUP THAT REPLACES A $3,000 AGENCY AND COSTS $59 A MONTH Microsoft and Google have been running this for a while - the gap against an agency is exactly 51x. an agency charged you for waiting, not for work - the brief walked from the strategist to the copywriter to the designer for weeks. here all 6 loops read one file on the same pass - there's nobody to wait on, and the calendar is empty. 51% of the bill is production on Sonnet 5, and only 5% is strategy on Opus 5 - the priciest model runs once a week. 22% of the whole bill sits on the batch queue at half rate - where nobody is waiting for an answer right now. the journal is the only loop that writes back into the root - which angle is dead, and next week starts tighter. the 6 loops bring you 3 angles a week - the final pick stays yours, and that's the part that never automates. save this and paste it into Claude Code - the loops remove the waiting, not the judgement ↓

Noisy

10,557 次观看 • 25 天前

Opus 5 (before) vs Opus 5 (now) I tested this rocket scene again after people started saying Opus 5 might be getting routed to Opus 5.2. And yeah, the difference is pretty clear. I know these models aren't deterministic, but I ran the same scene multiple times with Opus 5 before, and it never got this level of realism in one shot. If this is actually Opus 5.2, it could be a game-changing model for Anthropic. I’m starting to think Opus 5.2 could mog Astra in frontend and 3D.

Opus 5 (before) vs Opus 5 (now) I tested this rocket scene again after people started saying Opus 5 might be getting routed to Opus 5.2. And yeah, the difference is pretty clear. I know these models aren't deterministic, but I ran the same scene multiple times with Opus 5 before, and it never got this level of realism in one shot. If this is actually Opus 5.2, it could be a game-changing model for Anthropic. I’m starting to think Opus 5.2 could mog Astra in frontend and 3D.

Bhavy☄️

63,717 次观看 • 3 天前

ANTHROPIC LEAKED A FILE WHERE 4 AGENTS BUILD A BUSINESS DOING $100K A MONTH IN 60 MINUTES four agents run around the clock, cost $0 and work against a $100,000 target scout → architect → 2 builders → critic → back to root what makes it a team isn't the four agents, it's the three contracts written between them the scout hands the architect who already ships this and what they charge the architect hands the builders a spec with the interfaces named the builders hand the critic a diff and the tests that cover it leave any one of those boundaries vague and the work goes missing exactly there Haiku 4.5 triages cheap, Opus 5 decides expensive, Sonnet 5 builds, Opus 5 judges the most expensive model runs twice: once to plan, once to pass verdict two builders in parallel is two ways to disagree - which is exactly what the gate is for $100,000 is 334 customers at $299, $50,000 is 167, $10,000 is 34 and what you pay isn't even visible on that same scale the cost was never the thing standing in your way save this and paste it into Claude Code - let it write your 3 contracts ↓

ANTHROPIC LEAKED A FILE WHERE 4 AGENTS BUILD A BUSINESS DOING $100K A MONTH IN 60 MINUTES four agents run around the clock, cost $0 and work against a $100,000 target scout → architect → 2 builders → critic → back to root what makes it a team isn't the four agents, it's the three contracts written between them the scout hands the architect who already ships this and what they charge the architect hands the builders a spec with the interfaces named the builders hand the critic a diff and the tests that cover it leave any one of those boundaries vague and the work goes missing exactly there Haiku 4.5 triages cheap, Opus 5 decides expensive, Sonnet 5 builds, Opus 5 judges the most expensive model runs twice: once to plan, once to pass verdict two builders in parallel is two ways to disagree - which is exactly what the gate is for $100,000 is 334 customers at $299, $50,000 is 167, $10,000 is 34 and what you pay isn't even visible on that same scale the cost was never the thing standing in your way save this and paste it into Claude Code - let it write your 3 contracts ↓

Sprytix

140,042 次观看 • 2 天前

ANTHROPIC LEAKED A FILE THEY SPENT 4 YEARS BUILDING - IT CREATES A MARKETING AGENCY IN 60 MINUTES AND GENERATES $100K A MONTH agency charged $3,000 a month not for the work but for 3 weeks of waiting - the actual work in there is 4 hours. here 6 roles read one brief at the same moment, so there's nobody to wait on. you write 4 lines at the start: the client, the tone, the offer, what we never do. the fourth line is the one an agency needs 3 meetings to establish. Opus 5 sets the positioning, Sonnet 5 runs 3 branches for posts, landing and visuals, Haiku 4.5 sorts where and when it all gets published. 3 variants exist before you finish reading the first - choosing what ships was always the job. 15 cents a day decide which hour every post lands on - the same post at the wrong hour is a post nobody saw. analytics is the only role that writes back into the brief - which angle died and where not to go again. cut that link and the other 5 hammer the same dead angle for a month. 6 roles at $2 a day against $3,000 a month - a 50x gap, and production stops being the bottleneck. save this and paste it into Claude Code - the file does the production, the judgement stays yours ↓

ANTHROPIC LEAKED A FILE THEY SPENT 4 YEARS BUILDING - IT CREATES A MARKETING AGENCY IN 60 MINUTES AND GENERATES $100K A MONTH agency charged $3,000 a month not for the work but for 3 weeks of waiting - the actual work in there is 4 hours. here 6 roles read one brief at the same moment, so there's nobody to wait on. you write 4 lines at the start: the client, the tone, the offer, what we never do. the fourth line is the one an agency needs 3 meetings to establish. Opus 5 sets the positioning, Sonnet 5 runs 3 branches for posts, landing and visuals, Haiku 4.5 sorts where and when it all gets published. 3 variants exist before you finish reading the first - choosing what ships was always the job. 15 cents a day decide which hour every post lands on - the same post at the wrong hour is a post nobody saw. analytics is the only role that writes back into the brief - which angle died and where not to go again. cut that link and the other 5 hammer the same dead angle for a month. 6 roles at $2 a day against $3,000 a month - a 50x gap, and production stops being the bottleneck. save this and paste it into Claude Code - the file does the production, the judgement stays yours ↓

Sprytix

17,882 次观看 • 26 天前

ANTHROPIC LEAKED A FILE THAT BUILDS A 12-PERSON TEAM FOR $0 - AND THAT TEAM BUILDS A BUSINESS DOING $1.4M A YEAR a 12-person team would cost you $50,000 a month, this one costs exactly zero and shows a result in 5 days root → contracts → staff → gates → clock → back to root the root never describes the product, it describes who is going to build it the first hour writes the team, the next day that team writes the product Opus 5 sits on the architect and the critic, three Sonnet 5 build, one more tests Haiku 4.5 keeps the records, and the auditor rewrites the team rules, never the product $1.4M is either 400 customers at $292 a month, or 39 clients at $3,000 the staff is real and costs $792 a year, the revenue line above it is arithmetic the cascade builds the machine, it does not sign a single one of those numbers want a different product - you change the task, not rebuild the system demand is decided by the offer, never by the file save this and paste it into Claude Code - let it build your ROOT.md ↓

ANTHROPIC LEAKED A FILE THAT BUILDS A 12-PERSON TEAM FOR $0 - AND THAT TEAM BUILDS A BUSINESS DOING $1.4M A YEAR a 12-person team would cost you $50,000 a month, this one costs exactly zero and shows a result in 5 days root → contracts → staff → gates → clock → back to root the root never describes the product, it describes who is going to build it the first hour writes the team, the next day that team writes the product Opus 5 sits on the architect and the critic, three Sonnet 5 build, one more tests Haiku 4.5 keeps the records, and the auditor rewrites the team rules, never the product $1.4M is either 400 customers at $292 a month, or 39 clients at $3,000 the staff is real and costs $792 a year, the revenue line above it is arithmetic the cascade builds the machine, it does not sign a single one of those numbers want a different product - you change the task, not rebuild the system demand is decided by the offer, never by the file save this and paste it into Claude Code - let it build your ROOT.md ↓

Sprytix

39,041 次观看 • 12 天前

ANTHROPIC LEAKED A FILE THAT TURNS AN EMPTY FOLDER INTO A PRODUCT WITH A PRICE IN 60 MINUTES AND AIMS AT $100,000 A MONTH in one hour you get a product with a price on it - a startup burns a quarter and $80,000 for that same hour problem → shape → surface → price → machine → back to the problem you write only the first 12 minutes: who hurts, and what it costs them right now Opus 5 gives it a shape and then a price, three Sonnet 5 build three versions of the page Haiku 4.5 stands up the machine: delivery, the queue and the weekly numbers $100,000 a month is 1,000 customers at $100, or 10 at $10,000 same number, four completely different businesses which of those four rows you're standing on gets decided in minutes 36-48, not a year from now at minute sixty you have a product, a price and a machine - and 0 customers the hour compresses the first clock to nothing, it never touches the second one the hour makes the product, it does not make the demand save this and paste it into Claude Code - let it build you these 5 blocks ↓

ANTHROPIC LEAKED A FILE THAT TURNS AN EMPTY FOLDER INTO A PRODUCT WITH A PRICE IN 60 MINUTES AND AIMS AT $100,000 A MONTH in one hour you get a product with a price on it - a startup burns a quarter and $80,000 for that same hour problem → shape → surface → price → machine → back to the problem you write only the first 12 minutes: who hurts, and what it costs them right now Opus 5 gives it a shape and then a price, three Sonnet 5 build three versions of the page Haiku 4.5 stands up the machine: delivery, the queue and the weekly numbers $100,000 a month is 1,000 customers at $100, or 10 at $10,000 same number, four completely different businesses which of those four rows you're standing on gets decided in minutes 36-48, not a year from now at minute sixty you have a product, a price and a machine - and 0 customers the hour compresses the first clock to nothing, it never touches the second one the hour makes the product, it does not make the demand save this and paste it into Claude Code - let it build you these 5 blocks ↓

Noisy

14,460 次观看 • 10 天前

ANTHROPIC LEAKED A 3-SEAT SETUP WHERE THE BILL DROPS FROM $100 TO $21 AND SPEED GOES UP 3X engineers at Google and Microsoft have been running this for a while - they pay $21 where you pay $100. sorter → worker ×8 → judge → rejected → back to the worker every seat is a role you would otherwise have hired a person for - and none of the three adds headcount. Haiku throws 500 tasks a day into three buckets and doesn't think at all - anything you'd solve with a regex belongs on the cheapest seat. Sonnet carries the work across 8 parallel lanes 200 times a day - most of the bill lives right here. move this seat up one tier and the bill doubles with almost nothing to show for it. Opus runs only twice a day - expensive per turn and invisible on the bill. the author never grades its own work - Sonnet writes, Opus judges, rejected goes back. cut that judge to save money and you lose the only reason the cheap work is trusted. 3x isn't a faster model, it's eight lanes at once - you pay the latency of the slowest lane, not the sum of all. and the trap: 5x cheaper stops being true the second the cheap seat starts deciding. save this and paste it into Claude Code - and you get 3 seats instead of 3 hires ↓

ANTHROPIC LEAKED A 3-SEAT SETUP WHERE THE BILL DROPS FROM $100 TO $21 AND SPEED GOES UP 3X engineers at Google and Microsoft have been running this for a while - they pay $21 where you pay $100. sorter → worker ×8 → judge → rejected → back to the worker every seat is a role you would otherwise have hired a person for - and none of the three adds headcount. Haiku throws 500 tasks a day into three buckets and doesn't think at all - anything you'd solve with a regex belongs on the cheapest seat. Sonnet carries the work across 8 parallel lanes 200 times a day - most of the bill lives right here. move this seat up one tier and the bill doubles with almost nothing to show for it. Opus runs only twice a day - expensive per turn and invisible on the bill. the author never grades its own work - Sonnet writes, Opus judges, rejected goes back. cut that judge to save money and you lose the only reason the cheap work is trusted. 3x isn't a faster model, it's eight lanes at once - you pay the latency of the slowest lane, not the sum of all. and the trap: 5x cheaper stops being true the second the cheap seat starts deciding. save this and paste it into Claude Code - and you get 3 seats instead of 3 hires ↓

Sprytix

23,189 次观看 • 1 个月前

ANTHROPIC LEAKED A 6-AGENT ASSEMBLY LINE WHERE ONE PROMPT GOES IN AND A FINISHED PR COMES OUT your name shows up in this process exactly once - at the very end, for 5 minutes. prompt → planner → coder → tester → critic → scribe → PR Opus 5 plans once - a bad plan executed by five perfect agents is still a bad result. Sonnet 5 runs 3 parallel lanes - and they only work because the planner made the steps independent. tests loop until green and red goes back to the coder - the critic never sees a broken build. Opus 5 as the critic rejects to the plan, not the code - tests ask "does it run", the critic asks "should it exist". the PR description writes itself from the trace, not from memory - cut this seat and you get 8 PRs nobody can tell apart. one human step in the whole thing: approve or send back - 5 minutes instead of 5 hours. save the setup - 2 models, 6 seats, 2 return paths ↓

ANTHROPIC LEAKED A 6-AGENT ASSEMBLY LINE WHERE ONE PROMPT GOES IN AND A FINISHED PR COMES OUT your name shows up in this process exactly once - at the very end, for 5 minutes. prompt → planner → coder → tester → critic → scribe → PR Opus 5 plans once - a bad plan executed by five perfect agents is still a bad result. Sonnet 5 runs 3 parallel lanes - and they only work because the planner made the steps independent. tests loop until green and red goes back to the coder - the critic never sees a broken build. Opus 5 as the critic rejects to the plan, not the code - tests ask "does it run", the critic asks "should it exist". the PR description writes itself from the trace, not from memory - cut this seat and you get 8 PRs nobody can tell apart. one human step in the whole thing: approve or send back - 5 minutes instead of 5 hours. save the setup - 2 models, 6 seats, 2 return paths ↓

Sprytix

39,283 次观看 • 1 个月前

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

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

Danny Limanseta

36,419 次观看 • 5 个月前

I just had to make a new video of GLM-4.7-Flash - Helping me refactor VLLM studio - Did a data analytics report for work - Managed to search my tweets - Made me a fully playable Pacman in 1 shot - Great at browser use This model is too good to be this small, the full thing will fit on a macbook, it's fast, precise and can do pretty much anything Sonnet can. It somehow benches higher than Sonnet 4, 3.7, Opus 4.5 no thinking, all the GPT models from last year and more.

I just had to make a new video of GLM-4.7-Flash - Helping me refactor VLLM studio - Did a data analytics report for work - Managed to search my tweets - Made me a fully playable Pacman in 1 shot - Great at browser use This model is too good to be this small, the full thing will fit on a macbook, it's fast, precise and can do pretty much anything Sonnet can. It somehow benches higher than Sonnet 4, 3.7, Opus 4.5 no thinking, all the GPT models from last year and more.

0xSero

38,263 次观看 • 8 个月前

ANTHROPIC LEAKED A FILE THEY SPENT 4 YEARS AND $2.3M BUILDING - IT TAKES 60 MINUTES TO WRITE AND RUNS 30 DAYS WITHOUT YOU Microsoft and Google have been running this for a while - and they save $200,000 a month on it. across 30 days you show up exactly 3 times, and each one is a decision, not a task. the first 12 minutes you write 3 lines - all 4 blocks then read them every morning for a month. write them badly and the machine automates the wrong business perfectly, 30 times in a row. Opus 5 runs once a day and produces the offer - every block downstream quotes it. Sonnet 5 runs 3 branches and builds the landing page, payment link, auto-replies and analytics in 12 minutes. only 1 block out of 5 faces outward: 400 signals scored, 12 letters written, 3 answers, 1 payment. the other 4 blocks produce files - only that one produces a conversation. overnight Haiku 4.5 takes those 3 numbers and rewrites one line in the root - tomorrow the 400 get filtered tighter. without that line day 30 hunts exactly the way day 1 did. save this and paste it into Claude Code - the hour builds the machine, the offer decides the number ↓

ANTHROPIC LEAKED A FILE THEY SPENT 4 YEARS AND $2.3M BUILDING - IT TAKES 60 MINUTES TO WRITE AND RUNS 30 DAYS WITHOUT YOU Microsoft and Google have been running this for a while - and they save $200,000 a month on it. across 30 days you show up exactly 3 times, and each one is a decision, not a task. the first 12 minutes you write 3 lines - all 4 blocks then read them every morning for a month. write them badly and the machine automates the wrong business perfectly, 30 times in a row. Opus 5 runs once a day and produces the offer - every block downstream quotes it. Sonnet 5 runs 3 branches and builds the landing page, payment link, auto-replies and analytics in 12 minutes. only 1 block out of 5 faces outward: 400 signals scored, 12 letters written, 3 answers, 1 payment. the other 4 blocks produce files - only that one produces a conversation. overnight Haiku 4.5 takes those 3 numbers and rewrites one line in the root - tomorrow the 400 get filtered tighter. without that line day 30 hunts exactly the way day 1 did. save this and paste it into Claude Code - the hour builds the machine, the offer decides the number ↓

Sprytix

15,477 次观看 • 22 天前

Someone ran Claude Code on a beach where any device overheats and that spot suddenly turned out to be the best home for the most powerful AI in the world. This is the reMarkable Paper Pro. A paper tablet for notes with no browser and no social media and not a single app. He sat down right on the sand in the open sun and brought up Claude Code on Opus 4.6 over the Claude API on the paper screen and opened his project ~/repos/webs while the waves broke a few steps away. For years every device had the same trouble outside. In direct sun the screen glares and washes out and heats up and instead of your work you see your own reflection. But e-ink does not blast its own light into your face. It reflects the sunlight like the page of a book. And here is what came out of it. The very thing that kills any normal screen outside turned into fuel for this one. The brighter the sun the sharper the picture because it has nothing to glare with and nothing to wash out. And then comes the thing no laptop on a beach will give you. Your eyes do not get tired. You can watch Opus think on max effort for an hour and it reads like a book in the sun and not a backlight you squint into. The picture only comes alive. In bright light it does not fade but turns sharper and higher in contrast than it ever was in a room. The charge lasts for days. E-ink barely touches the battery so there is no outlet anywhere on the sand and the tablet does not care. It weighs as much as a notebook. The whole setup folds into a beach bag like a pad with a pen on top. Everything on the screen is for real. Claude Code v2.1.110 and Opus 4.6 on the Claude API and the project ~/repos/webs open right on the e-ink in the middle of the sand. In my opinion this is the most unexpected home for an AI this year. Not an office with the blinds drawn and not a monitor cranked to full brightness but a quiet sheet of paper on the sand that open sun only makes better and on it the most powerful Claude writes code right on the page like a pen.

Someone ran Claude Code on a beach where any device overheats and that spot suddenly turned out to be the best home for the most powerful AI in the world. This is the reMarkable Paper Pro. A paper tablet for notes with no browser and no social media and not a single app. He sat down right on the sand in the open sun and brought up Claude Code on Opus 4.6 over the Claude API on the paper screen and opened his project ~/repos/webs while the waves broke a few steps away. For years every device had the same trouble outside. In direct sun the screen glares and washes out and heats up and instead of your work you see your own reflection. But e-ink does not blast its own light into your face. It reflects the sunlight like the page of a book. And here is what came out of it. The very thing that kills any normal screen outside turned into fuel for this one. The brighter the sun the sharper the picture because it has nothing to glare with and nothing to wash out. And then comes the thing no laptop on a beach will give you. Your eyes do not get tired. You can watch Opus think on max effort for an hour and it reads like a book in the sun and not a backlight you squint into. The picture only comes alive. In bright light it does not fade but turns sharper and higher in contrast than it ever was in a room. The charge lasts for days. E-ink barely touches the battery so there is no outlet anywhere on the sand and the tablet does not care. It weighs as much as a notebook. The whole setup folds into a beach bag like a pad with a pen on top. Everything on the screen is for real. Claude Code v2.1.110 and Opus 4.6 on the Claude API and the project ~/repos/webs open right on the e-ink in the middle of the sand. In my opinion this is the most unexpected home for an AI this year. Not an office with the blinds drawn and not a monitor cranked to full brightness but a quiet sheet of paper on the sand that open sun only makes better and on it the most powerful Claude writes code right on the page like a pen.

Blaze

89,575 次观看 • 2 个月前

you were in the middle of something and it compacted, and you took that for the limit it was a default, and it is almost certainly not the number you think it is on a two hundred thousand window it fires near two hundred thousand, but on sonnet 5, the fable models and opus 4.7 and later it fires near nine hundred and sixty seven thousand, behind an llm gateway that same model is held down to two hundred thousand unless you pick the one million entry by hand so the moment your work gets summarized is decided by a model id string, and when that string is an alias the client does not recognise, it guesses autoCompactWindow in settings takes 150k and holds it CLAUDE_CODE_MAX_CONTEXT_TOKENS stops the guessing you did not hit a ceiling you accepted one

you were in the middle of something and it compacted, and you took that for the limit it was a default, and it is almost certainly not the number you think it is on a two hundred thousand window it fires near two hundred thousand, but on sonnet 5, the fable models and opus 4.7 and later it fires near nine hundred and sixty seven thousand, behind an llm gateway that same model is held down to two hundred thousand unless you pick the one million entry by hand so the moment your work gets summarized is decided by a model id string, and when that string is an alias the client does not recognise, it guesses autoCompactWindow in settings takes 150k and holds it CLAUDE_CODE_MAX_CONTEXT_TOKENS stops the guessing you did not hit a ceiling you accepted one

Lagosaur

11,662 次观看 • 7 天前

Today, we’re releasing Athena (mvrko-sim-1), the flagship Large Event Model from markopolo.ai that beats GPT-5.6, Claude Opus 4.8, and Claude Sonnet 5 in OPeRa public benchmark for Shopping behaviour prediction! Athena introduces a completely different approach to understanding digital behavior. Most systems record actions after they happen. Athena models the sequence behind them to predict what a shopper will do next and exactly where they will do it, before the action even takes place. Athena vs. frontier models: We evaluated Athena on the full OPeRA test set alongside GPT-5.6, GPT-4.1, Claude Sonnet 5, and Claude Opus 4.8. Athena achieved 24.5% strict exact match scoring the highest among the five models evaluated. Athena is not a general-purpose language model. It is a Large Event Model built to understand behavior as a connected sequence. It combines the page someone is viewing, the actions that brought them there, and the goal they are trying to complete and then predicts the exact next browser action and target element. That distinction matters. Today’s digital systems largely react after someone clicks, abandons, purchases, or leaves. Athena creates the foundation for systems that can understand what is likely to happen before the outcome. Together with Rubaiyat, and the team at markopolo.ai, we built Athena from years of work on shopper behavior, digital journeys, and behavioral intelligence. Commerce was our first proving ground. Great thing is, we’re now releasing Athena publicly so builders can adapt the model to new datasets, industries, and problems. We’re seeing early usecases in Cyber Security, Gaming, Mobile App Ecosystem, Retail and more! Athena is now live on Hugging Face! We built the foundation for relevance and predictability! Now, let’s see what the world builds on top of it. Links in the first reply.

Today, we’re releasing Athena (mvrko-sim-1), the flagship Large Event Model from markopolo.ai that beats GPT-5.6, Claude Opus 4.8, and Claude Sonnet 5 in OPeRa public benchmark for Shopping behaviour prediction! Athena introduces a completely different approach to understanding digital behavior. Most systems record actions after they happen. Athena models the sequence behind them to predict what a shopper will do next and exactly where they will do it, before the action even takes place. Athena vs. frontier models: We evaluated Athena on the full OPeRA test set alongside GPT-5.6, GPT-4.1, Claude Sonnet 5, and Claude Opus 4.8. Athena achieved 24.5% strict exact match scoring the highest among the five models evaluated. Athena is not a general-purpose language model. It is a Large Event Model built to understand behavior as a connected sequence. It combines the page someone is viewing, the actions that brought them there, and the goal they are trying to complete and then predicts the exact next browser action and target element. That distinction matters. Today’s digital systems largely react after someone clicks, abandons, purchases, or leaves. Athena creates the foundation for systems that can understand what is likely to happen before the outcome. Together with Rubaiyat, and the team at markopolo.ai, we built Athena from years of work on shopper behavior, digital journeys, and behavioral intelligence. Commerce was our first proving ground. Great thing is, we’re now releasing Athena publicly so builders can adapt the model to new datasets, industries, and problems. We’re seeing early usecases in Cyber Security, Gaming, Mobile App Ecosystem, Retail and more! Athena is now live on Hugging Face! We built the foundation for relevance and predictability! Now, let’s see what the world builds on top of it. Links in the first reply.

Tasbin

55,854 次观看 • 1 个月前