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rgbrenner 1 hours ago [-]
Forget about the scores... look at the Cost Per Task. Fable 5.1 was already the most expensive by a good margin, and now Fable 5.2 doubles it! This is with the price cut.
The output tokens per task just exploded. From 118k tokens (46k Answer/71k Reasoning) in 5.1 to 274k tokens (81k Answer/192k Reasoning) in 5.2.
Loquebantur 54 minutes ago [-]
They have maxed out the base data with the given model architecture and scale "intelligence" through inference-based RL.
Notably, in order to achieve a specific quality, the model has to "reason" for every prompt proportional to the training inference.
This is arguably the case of diminishing returns being reached, as answer token prices saturate the willingness of customers to pay.
They've run into a wall.
sebzim4500 50 minutes ago [-]
There's a whole frontier of cost vs performance and this model pushes it out in a bunch of places, so its not just a matter of making a different tradeoff as you make it sound.
Loquebantur 35 minutes ago [-]
What you're looking at there is the cost/performance in inference. The "frontier".
An economically successful step would be to improve training cost/frontier advance.
They essentially failed at that, assuming they kept their training costs for the model step at least constant.
rsalus 6 minutes ago [-]
isn't that what Opus is for? this is the "strongest" model, not the most economical
mattnewton 24 minutes ago [-]
Maybe a dumb question but once you have a model that spends a lot of tokens for high performance why can’t you distill it into a model that thinks less?
Sure it wouldn’t generalize well to new tasks but plenty of tasks are important and recurrent enough to justify this
buckle8017 21 minutes ago [-]
The reasoning/thinking is basically trying many many different branches.
To do that you need a larger model to have many many branches to try.
mirekrusin 36 minutes ago [-]
There are tasks that people will easily pay hundreds or thousands of dollars per pop.
And maybe that's how all of it is going to evolve in the future – so you pay per solution, not tokens?
Loquebantur 31 minutes ago [-]
Diminishing returns would catch you there as well.
Perhaps, it's a bit like being a super smart person in contemporary society: at some point, being smarter doesn't really reliably translate into a better life.
When you learn from available human data, those text books max out at some point. You cannot learn what isn't there.
rowanG077 11 minutes ago [-]
How do you explain Opus 5.5 or GPT 6.1? I could maybe agree if this is a general trend. But one supermodel existing that is really expensive does not signal diminishing returns.
lnenad 50 minutes ago [-]
That would be my layman's assumption as well. A theory is they're just releasing this as a stepping stone towards something bigger before the IPO. Either way it's the same way chinese models get higher scores on benchmarks. Drop enough of wait actuallys and you'll be top the charts, but time per task and tokens per task go up by a mile (as is the case with this release).
35 minutes ago [-]
suddenlybananas 33 minutes ago [-]
This would be great for my sanity.
onlyrealcuzzo 47 minutes ago [-]
If you compare Fable 5.2 Medium to Opus 5.5 high (settings that make sense - max is universally considered rarely worth it), you will see that Fable 5.2 is SUPPOSEDLY very cost competitive: https://artificialanalysis.ai/models/claude-fable-5-2?models...
goldenarm 20 minutes ago [-]
Fable 5.2 is much cheaper per successful task though.
Fable 5.2 low is 3x cheaper than Fable 5.1 xhigh while being 8% smarter.
In case you're unaware, this is for the max setting. The (recommmended) high setting uses only 80k tokens.
lifeisloving 51 minutes ago [-]
Its still prohibitively expensive, and models 5% the cost are faster and get the job done just as well (for the average person's workflow).
I really don't get the value proposition of these massive models, seems like they're just loss leaders simply to say you're the in the top 3. There's not much use cases outside of niche academic research (and even then I question the need). They mostly function as marketing tools, like a casino that offers high roller accommodations.
People will say "cyber" but companies didnt want to spend on security before, not sure why they would all of a sudden be compelled to spend even more.
svachalek 11 minutes ago [-]
Not everyone is writing CRUD business apps and personal use software. Pretty much any model can do those now. The frontier is for doing things those models struggle with. Even in vibe coding a simple video game the difference in results between an open source model, the previous frontier model, and the current model is pretty huge.
Security is mandatory now in a way that it wasn't, now that AI has eliminated the skill barrier to hacking.
artemisart 8 minutes ago [-]
People looking at frontier models release are not the average person, and let's say that you pay $150 with Fable to save $1000, it's much more interesting than using $10 with a cheap model to save even $500.Scale numbers to whatever suits you.
kolinko 12 minutes ago [-]
Well for tasks that can be done with another model you just use another model.
persedes 51 minutes ago [-]
^ and even at medium it is juuuust outside their "Most attractive quadrant"
nekoashide 51 minutes ago [-]
I think we will beat the cost with Hardware. Faster, more efficient hardware. From what I have seen we have only found ways to make it smarter and not more cost effective.
I'm curious to see the next generation of dedicated AI processors and how they perform.
danuker 36 minutes ago [-]
There are models offering great value on current hardware, like GLM-5.3-Flash and DeepSeek-v4.1-1017.
Anthropic and OpenAI are expensive bleeding edge, but few use cases really need it.
Bluestein 31 minutes ago [-]
At this point, they are beginning to approach the Tesla Roadster case. The flying one.-
iknownthing 36 minutes ago [-]
I'd rather a model be super expensive and cure cancer than not exist at all
platinumrad 26 minutes ago [-]
This would be a much more insightful comment if the model actually cured cancer.
iknownthing 17 minutes ago [-]
Seriously though, does every model have to be affordable? Can't there be a model analogue of a rolex/ferrari?
airza 59 minutes ago [-]
It beats opus 5.5's max effort with less cost, which is a step forward if you don't want to crank it to Ultra Max Settings.
The amount of compute it cost to get the best previous performance from anthropic went down. Nobody is putting a gun to your head and forcing you to go further down the paretto frontier if the current level of intelligence/task is acceptable to you.
eterm 37 minutes ago [-]
I saw one benchmark where Opus 5.5 max benched worse than opus 5.5 high, using "max" on any model seems foolish, but for opus 5.5 especially, where it seems to degrade at xhigh and max.
Cheaper and faster than Opus(max) AND scored higher. But yeah let's doompost about it...
datadrivenangel 56 minutes ago [-]
The frontier chart there makes gemini carbon look really weird. Low is worse and more expensive than medium, and high is worse and more expensive than medium... funky curve like that implies a messed up model or weird benchmark.
softboyled 8 minutes ago [-]
"particularly expensive when comparing to other models of similar price"
johnnyApplePRNG 15 minutes ago [-]
So it's basically the same model just with gargantuan reasoning enabled?
Booooooooooo!
xienze 1 hours ago [-]
Well they do have an IPO coming up.
mordymoop 1 hours ago [-]
Most people never run out of plan usage, so the cost per task matters relatively little.
smoe 56 minutes ago [-]
Plan usage is available for companies with 2–150 seats. Above that, it's usage-based billing.
Iolaum 53 minutes ago [-]
Does that mean bigger companies can only get API pricing?
smoe 45 minutes ago [-]
That's my understanding, yes. But not sure what kind of deals the larger clients can negotiate.
> US$20/seat/month, billed annually, 20 seat minimum. Usage cost scales with model and task.
There is no premium seat option listed for the enterprise plan
oh_no 1 hours ago [-]
1. a lot of people do
2. most of their revenue comes from api pricing
mordymoop 1 hours ago [-]
Those are both true, but I don't see how they are meant to rebut what I said.
Most people on plan use do NOT use up all their plan usage.
Users on API plans can still use Opus 5.5 which is a great model. If they want top of the line performance, they can pay more.
When another company puts out a model that undercuts Fable 5.2 on price at similar performance, Anthropic will put out Opus 6 and undercut them right back. That's how the wheel turns. This is just part of the cycle.
qeternity 55 minutes ago [-]
It rebuts what you said because your statement that "the cost per task matters relatively little" is not true in the slightest.
This might be true for a small portion of the user base, but it is not true as a statement of fact.
kjuulh 58 minutes ago [-]
Most is doing the heavy lifting here. I am a power user. And I max 3 claude max subscriptions on opus 5.5 high and a single codex pro 5x for personal use.
I am always interested in this comparison since it shows how quickly you can go back and forth with a model, capturing both tokens/task and tokens/second. The new models seem to be meaningfully better here.
jrflo 52 minutes ago [-]
Why does AA choose ~$3.1 per task to be the breaking point for "most attractive quadrant" highlight? Surely the most attractive section is just being close to the entire frontier?
StevenWaterman 50 minutes ago [-]
It's a quarter of the graph (hence quadrant)
jrflo 29 minutes ago [-]
The choice of X-axis maximum and Y-axis maximum dictates the cutoff point of the quadrant. With a maximum of $80 per task, the quadrant is $3.1 and lower. If some new model gets released and costs more than $80 per task, the "most attractive" cutoff moves up from $3.1 since they have to move the X-axis max. It's completely arbitrary.
StevenWaterman 17 minutes ago [-]
It's not saying that being inside that quadrant is a hard cut-off it's just illustrating the direction of the pareto frontier
If you take the average point inside the 4 quadrants, the top left one is pareto optimal (of the 4)
jgalt212 58 minutes ago [-]
> it shows how quickly you can go back and forth with a model
Another member of the pro-REPL / anti-agentic tribe. There are dozens of us!
schnitzelstoat 14 minutes ago [-]
That seems like an insane increase in cost for a modest intelligence increase.
But perhaps the performance on real-world tasks will be more noticeable than on benchmarks.
gizmodo59 1 hours ago [-]
https://artificialanalysis.ai/#intelligence-efficiency-tabs this is the chart that matters for most of poor developers and companies. Pareto for a given intelligence index and looks like only openai is across the quadrant with muse at the bottom. They have really cooked efficient models!
origini 36 minutes ago [-]
It depends on the task though. If your cheap task can't solve it
mutech53 15 minutes ago [-]
I am wondering which use cases would require usage from Fable 5.2 especially when Opus 5.5 already performs almost all of the tasks in a very optimized way.
copperx 5 minutes ago [-]
[delayed]
qntty 2 hours ago [-]
Crazy how quick these are coming out now
jrflo 1 hours ago [-]
I'm sure that they get early access to run the benchmarks, it wouldn't have time to finish running if they were running it at public release
AnotherGoodName 1 hours ago [-]
Someone on a thread was complaining they haven’t really needed the newer models because Opus 4.6 was good enough.
I had to remind them 4.6 only came out February this year. In a normal world 4.6 is a newer model! A model 6 months old is seen as ancient!
coderenegade 26 minutes ago [-]
Reminds me a lot of the race for clock speed when I was a kid. We just took it for granted that it was going to keep increasing, but CPUs sat at roughly 1-2GHz for a long time, or at least that's how it seemed. The slowdown and pause was fairly noticeable. The current release cadence is unsustainable. It might be that we're getting close to the AI equivalent of 1-2GHz CPUs, and it takes years of incremental progress to push further.
vbroot 26 minutes ago [-]
It does not seem profitable as those prices.
suddenlybananas 2 hours ago [-]
Why is it so much more expensive?
nsingh2 2 hours ago [-]
This page is showing Max effort, which is much more expensive.
Max should not be used unless you really need every bit of perf, it's deep into diminishing returns territory.
1 hours ago [-]
dgellow 2 hours ago [-]
It seems to use way, way more tokens to complete the tasks
Tadpole9181 1 hours ago [-]
On max.
Change the models in the dropdown to medium / high and Fable 5.2 is about twice as cost efficient, and slightly faster.
persedes 55 minutes ago [-]
It's insane how people nitpick on the highest thinking setting for every anthropic release and claim it's too expensive. Not trying to stan for anthropic, but what am I missing here: Just don't use those models on the highest thinking setting?
Fable 5.2 medium for example seems a really good choice when it comes to the performance vs task (if you have a complex task that requires such a model of course).
njovin 1 hours ago [-]
This has got to be a minor reason why adoption of AI isn’t faster.
Businesses like predictable costs and predictable performance.
If your new model is slightly better but crazy expensive, but doesn’t have to be with certain settings, but my user can accidentally run it that way by mistake or maybe your harness makes it the default by accident and the user doesn’t notice…
My beloved predictability is destroyed and trying to get users to understand this is useless.
Imagine a streaming subscription that worked like this: “We’ve updated our catalog with more movies. If you want the premium ones though you only get 2 per week and then you have to wait. But if you do mostly classics and a few from the 2010s you can squeeze in a recent theater release. If you time it right and do only one every day you can see 30 modern classics this month, but you can’t watch three today. Also your bill this month is $40 instead of $20 due to the library update”.
santoshalper 1 hours ago [-]
Yep, and now multiply that complexity by hundreds or thousands of employees. That's why companies are giving in to crude, hacky solutions like monthly billing caps. What else are you really gonna do?
ProblemExplorer 59 minutes ago [-]
Fable, for me (it might be a completely different experience for you) has been like the well read snobbish kid at school that openly ignores me when I ask certain questions and often asks me to talk to someone else on other questions.
That kid might indeed be a genius, clearly bright, but is more interested in deciding whether I should have asked a question than in answering it.
For me personally, if the best model on the planet refuses to answer why I shouldn't mix bleach and ammonia, where I'm trying to understand the chemistry behind the warning, it's not pareto frontier to one that atleast tries to and points me in a general direction. Being told that the topic is concerning, referred to someone else and charged part of my quota for that experience feels like getting an invoice from that school genius for telling me to "just ask the chemistry teacher".
If my LLM asks me to rethink my life when I ask it to reverse engineer the firmware of my Samsung TV that I suspect is setting up adhoc radio networks to relay my data to Samsung's cloud, I feel rather sad, specially when that kid sends me an invoice for saying "no"
At least Anthropic should not bill me for the refusal (as of my last tests, refusals still comes out of my quota) - getting slapped and pickpocketed for asking a question is really upsetting.
baq 9 minutes ago [-]
fable is a high agency model (some people call it 'big model smell'). if you want something that blindly follows instructions, use sonnet. I want to be challenged by the thing since I expect it to be smarter than me at everything except the little part of human knowledge I'm an actual expert in.
cma 55 minutes ago [-]
>At least Anthropic should not bill me for the refusal (as of my last tests, refusals still comes out of my quota)
There's a setting to not degrade to a lower model on refusals and instead pause the chat.
demo4567 10 minutes ago [-]
Doesn't make it any better. If I refused to do a job, then I would be fired.
baq 8 minutes ago [-]
good thing these things aren't employed then right?
qwerpy 28 minutes ago [-]
Similar experience with Opus. Asked it to tighten access controls and isolation in my homelab. Designed something with a whole bunch of words that looked plausible, so I told it to go ahead. Halfway through it gets stuck because it locked itself out of something, and asks me to run some commands as root.
Me: No, I'm away from the computer right now, you figure it out. Use the root login you already have if you can't figure it out.
Opus: This can wait until you get home, then.
Me: No, figure it out now or use root.
Got [cyber]'d, some scary message that referred me to legal/AUP, and refused to continue.
Switched to OpenAI in part due to this silliness. Sol seems a little less smart but doesn't get on a high horse to lecture you about this stuff. It either does the work or fails to do the work, and leaves the moralizing out of it. It was able to take over from where Claude left off and finish the project.
Daunk 40 minutes ago [-]
Don't worry, it'll soon get dumbed down in a few weeks :)
Aurornis 28 minutes ago [-]
The Artificial Analysis charts are great, but be warned that they show max effort by default.
Max effort is nice for revealing the limits of a model, but it's almost never used in practice.
If you scroll down to the coding charts you can start adding Fable 5.2, Opus 5.5, and others at more normal difficulty settings.
Fable 5.2 on medium looks quite attractive compared to Opus 5.5 high/xhigh
Fable 5.2 on max (the default) looks like a good way to light your money on fire.
A_D_E_P_T 2 hours ago [-]
Google could have been #1 for a little while, but they botched their release and squandered their temporary lead. (As usual.) If I worked there, I'd be so pissed.
1 hours ago [-]
dhish3682 51 minutes ago [-]
[dead]
theplumber 1 hours ago [-]
So is Google still in the race? Does anyone actually uses Aragon or Carbon or whatever model they released for coding?
onlyrealcuzzo 36 minutes ago [-]
I use Argon regularly.
Pretty big Gemini fan - but IMO Argon is universally worse for coding than Astra or Opus 5.5 (un-nerfed).
I strongly prefer Gemini's output compared to anything else. So I typically use Argon to either direct other agents or explain something without psychobabble.
Argon/Carbon have by far the lowest hallucination rates, so IMO it serves as the best bullshit shield from other models.
In terms of implementation (and especially design), it's far behind Astra and Opus, and I'm sure Fable will make that gap even larger.
Argon/Carbon may give you not-the-best advice, but they are far less likely to just flat-out-and-completely lie to you.
skerit 1 hours ago [-]
Can you actually use it through some subscription, or only through the API?
iamdelirium 32 minutes ago [-]
Yes? I regularly use Argon in agy on my Google One subscription.
glimshe 1 hours ago [-]
I tried using it as part of my Pro/One/whatever subscription (the one that comes with Youtube Lite). For code review, it was able to find some things that Sol 6.1 couldn't. I found it quite useful. But for code generation, it's pathetically slow and the code isn't impressive. It's at least one year behind.
mattlondon 1 hours ago [-]
I do. I prefer it to Opus 5.5 - just as good at coding for my needs, but so much more pleasant to work with.
I am not sure how people keep saying google are not in the race, or have lost it or whatever when just a few hours ago they had the #1 model? What more do people want?
drusepth 1 hours ago [-]
I actually just think it's a meme to talk down on Gemini at any opportunity here. There's probably a fair number of people that wrote off antigravity at its (pretty rocky) launch. And Google also doesn't provide any kind of good sandbox-y experience to Just Try their models, which probably bites them here too.
But Gemini models are still neck and neck in the lead both in my experience and in benchmarks, and Gemini is far above the competitors (although Opus 5.5 closed much of the gap) when it comes to any kind of complex web dev. (I generally use Astra for anything 3D, Gemini for anything web/mobile, and Opus for everything else.)
pell 59 minutes ago [-]
Their latest internal reshuffling and the strange amount of parallel releases with the same target, their kafkaesque barriers to entry, and a lack of clear vision is what makes people think they’re not in the race anymore. Obviously they still are. They develop new models and also are deep in the compute game too.
theplumber 55 minutes ago [-]
In my experience Google models have always been mediocre at best and dangerous to use at worst but I must admit that I didn’t try the latest Aragon/carbon crop.
I learned not to put too much trust into benchmarks. The best benchmark is to use the model on a codebase you know well.
Tadpole9181 59 minutes ago [-]
On both Gemini 4 releases, it said on the release page that I cannot use it. No timeline as given and I have not seen an announcement otherwise since.
So, what more do I want? It'd be a good start to actually tell me it's available and giving me a clear path to using it via plan & harness?
oh_no 1 hours ago [-]
> What more do people want?
well, releasing it would be nice
mattlondon 13 minutes ago [-]
Gemini 4 Argon is available in both anti-gravity and the Gemini app for me on my Gmail account and I didn't do anything special (I have a modest drive storage subscription - not the largest nor smallest... Not sure if it is bundled with that or not).
So certainly released to the unwashed masses like me to use for free without any special extra work or API keys.
margalabargala 51 minutes ago [-]
I'll have to take your word for it, considering the latest model I'm able to use of theirs is 3.8 Flash for some reason.
krona 1 hours ago [-]
Optics and incentives. Google will turn on the R&D the day after their Anthropic investment is realised, maybe $80-150bn on a 1.2tn valuation, plus >100bn in spending commitments.
pmdr 55 minutes ago [-]
Splendid. Now how many prompts in you're downgraded to Opus 4.8 and then the chat is ended altogether?
aleqs 18 minutes ago [-]
Artificial Intelligence is bullshit. There, I said it.
demo4567 11 minutes ago [-]
Imo it is good at search and aggregate similar data. Intelligence it is not.
The output tokens per task just exploded. From 118k tokens (46k Answer/71k Reasoning) in 5.1 to 274k tokens (81k Answer/192k Reasoning) in 5.2.
Notably, in order to achieve a specific quality, the model has to "reason" for every prompt proportional to the training inference.
This is arguably the case of diminishing returns being reached, as answer token prices saturate the willingness of customers to pay.
They've run into a wall.
An economically successful step would be to improve training cost/frontier advance.
They essentially failed at that, assuming they kept their training costs for the model step at least constant.
To do that you need a larger model to have many many branches to try.
And maybe that's how all of it is going to evolve in the future – so you pay per solution, not tokens?
Perhaps, it's a bit like being a super smart person in contemporary society: at some point, being smarter doesn't really reliably translate into a better life.
When you learn from available human data, those text books max out at some point. You cannot learn what isn't there.
Fable 5.2 low is 3x cheaper than Fable 5.1 xhigh while being 8% smarter.
https://artificialanalysis.ai/?releases=claude-fable-5-2%2Cc...
1 - https://bench.killswitch-lang.org/
I really don't get the value proposition of these massive models, seems like they're just loss leaders simply to say you're the in the top 3. There's not much use cases outside of niche academic research (and even then I question the need). They mostly function as marketing tools, like a casino that offers high roller accommodations.
People will say "cyber" but companies didnt want to spend on security before, not sure why they would all of a sudden be compelled to spend even more.
Security is mandatory now in a way that it wasn't, now that AI has eliminated the skill barrier to hacking.
I'm curious to see the next generation of dedicated AI processors and how they perform.
Anthropic and OpenAI are expensive bleeding edge, but few use cases really need it.
The amount of compute it cost to get the best previous performance from anthropic went down. Nobody is putting a gun to your head and forcing you to go further down the paretto frontier if the current level of intelligence/task is acceptable to you.
Cheaper and faster than Opus(max) AND scored higher. But yeah let's doompost about it...
Booooooooooo!
https://support.claude.com/en/articles/9266767-what-is-the-t...
> Team plans support up to 150 seats. If your organization is on the Team plan and needs more than 150 seats, you can upgrade to the Enterprise plan.
https://claude.com/pricing
> Enterprise: Seat price + usage at API rates
> US$20/seat/month, billed annually, 20 seat minimum. Usage cost scales with model and task.
There is no premium seat option listed for the enterprise plan
Most people on plan use do NOT use up all their plan usage.
Users on API plans can still use Opus 5.5 which is a great model. If they want top of the line performance, they can pay more.
When another company puts out a model that undercuts Fable 5.2 on price at similar performance, Anthropic will put out Opus 6 and undercut them right back. That's how the wheel turns. This is just part of the cycle.
This might be true for a small portion of the user base, but it is not true as a statement of fact.
I am always interested in this comparison since it shows how quickly you can go back and forth with a model, capturing both tokens/task and tokens/second. The new models seem to be meaningfully better here.
If you take the average point inside the 4 quadrants, the top left one is pareto optimal (of the 4)
Another member of the pro-REPL / anti-agentic tribe. There are dozens of us!
But perhaps the performance on real-world tasks will be more noticeable than on benchmarks.
I had to remind them 4.6 only came out February this year. In a normal world 4.6 is a newer model! A model 6 months old is seen as ancient!
Max should not be used unless you really need every bit of perf, it's deep into diminishing returns territory.
Change the models in the dropdown to medium / high and Fable 5.2 is about twice as cost efficient, and slightly faster.
Fable 5.2 medium for example seems a really good choice when it comes to the performance vs task (if you have a complex task that requires such a model of course).
Businesses like predictable costs and predictable performance.
If your new model is slightly better but crazy expensive, but doesn’t have to be with certain settings, but my user can accidentally run it that way by mistake or maybe your harness makes it the default by accident and the user doesn’t notice…
My beloved predictability is destroyed and trying to get users to understand this is useless.
Imagine a streaming subscription that worked like this: “We’ve updated our catalog with more movies. If you want the premium ones though you only get 2 per week and then you have to wait. But if you do mostly classics and a few from the 2010s you can squeeze in a recent theater release. If you time it right and do only one every day you can see 30 modern classics this month, but you can’t watch three today. Also your bill this month is $40 instead of $20 due to the library update”.
That kid might indeed be a genius, clearly bright, but is more interested in deciding whether I should have asked a question than in answering it.
For me personally, if the best model on the planet refuses to answer why I shouldn't mix bleach and ammonia, where I'm trying to understand the chemistry behind the warning, it's not pareto frontier to one that atleast tries to and points me in a general direction. Being told that the topic is concerning, referred to someone else and charged part of my quota for that experience feels like getting an invoice from that school genius for telling me to "just ask the chemistry teacher".
If my LLM asks me to rethink my life when I ask it to reverse engineer the firmware of my Samsung TV that I suspect is setting up adhoc radio networks to relay my data to Samsung's cloud, I feel rather sad, specially when that kid sends me an invoice for saying "no"
At least Anthropic should not bill me for the refusal (as of my last tests, refusals still comes out of my quota) - getting slapped and pickpocketed for asking a question is really upsetting.
There's a setting to not degrade to a lower model on refusals and instead pause the chat.
Me: No, I'm away from the computer right now, you figure it out. Use the root login you already have if you can't figure it out.
Opus: This can wait until you get home, then.
Me: No, figure it out now or use root.
Got [cyber]'d, some scary message that referred me to legal/AUP, and refused to continue.
Switched to OpenAI in part due to this silliness. Sol seems a little less smart but doesn't get on a high horse to lecture you about this stuff. It either does the work or fails to do the work, and leaves the moralizing out of it. It was able to take over from where Claude left off and finish the project.
Max effort is nice for revealing the limits of a model, but it's almost never used in practice.
If you scroll down to the coding charts you can start adding Fable 5.2, Opus 5.5, and others at more normal difficulty settings.
Fable 5.2 on medium looks quite attractive compared to Opus 5.5 high/xhigh
Fable 5.2 on max (the default) looks like a good way to light your money on fire.
Pretty big Gemini fan - but IMO Argon is universally worse for coding than Astra or Opus 5.5 (un-nerfed).
I strongly prefer Gemini's output compared to anything else. So I typically use Argon to either direct other agents or explain something without psychobabble.
Argon/Carbon have by far the lowest hallucination rates, so IMO it serves as the best bullshit shield from other models.
In terms of implementation (and especially design), it's far behind Astra and Opus, and I'm sure Fable will make that gap even larger.
Argon/Carbon may give you not-the-best advice, but they are far less likely to just flat-out-and-completely lie to you.
I am not sure how people keep saying google are not in the race, or have lost it or whatever when just a few hours ago they had the #1 model? What more do people want?
But Gemini models are still neck and neck in the lead both in my experience and in benchmarks, and Gemini is far above the competitors (although Opus 5.5 closed much of the gap) when it comes to any kind of complex web dev. (I generally use Astra for anything 3D, Gemini for anything web/mobile, and Opus for everything else.)
I learned not to put too much trust into benchmarks. The best benchmark is to use the model on a codebase you know well.
So, what more do I want? It'd be a good start to actually tell me it's available and giving me a clear path to using it via plan & harness?
well, releasing it would be nice
So certainly released to the unwashed masses like me to use for free without any special extra work or API keys.