> Communication. Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5. It puts the most important information up front, and its style makes it a better work partner over long sessions. As one early tester put it, “it writes the way I do.” In our own use, this has made Opus 5.5’s work easier to follow and check—which is a safety benefit as well as a practical one.
I think this is what I'm most interested in. I mostly moved to Astra because I just can't work all day with the Claude Opus 5/Fable writing style. I don't think Astra is a better model, but it's the first OpenAI one that seemed good enough to me. Definitely keen to try Opus 5.5 and see if this claim is real.
Yes this is a big part of what has turned me off Opus 5 completely. The other (more dangerous) one is how often it gets assumptions wrong. These both (along with Astra) caused me to split my time 50/50 now between the two models.
Not a day goes by when I push back on something, to which Opus 5 very unambiguously say "You were right, I was wrong" - this never happened so often with past models, nor with Fable.
We'll have to see how much Opus's ability to communicate has improved. It's already giving me better summaries of where we are in the conversation.
I did the same switch (that reason along with the newer models seeming more "lazy" and needing constant prodding to finish long-horizon tasks) but my issue with ChatGPT/Codex now is that it too roundabout and doesn't get to the point. I tried adding instructions and using the personalization settings to make it more efficient but haven't seen much change. Claude seemed to follow settings more closely. Has anyone had any success to make ChatGPT more succinct?
I've been using Opus 5 since it was released and don't understand all the hate it gets. It very well could be something in my own local memories or Claude.MD files that prevents it, but I certainly have never experienced something like that site portrays.
You are right and make an important insight. While well meaning and amusing, it did not reflect the entire spectrum of outcomes that could arise from the worktree.
Navigating the landscape of agentic levers certainly requires a more detailed approach than this and you were certainly correct to push back.
> hi, can you explain how the scheduler works. keep it brief, but include important correctness details
some excerpts:
>Flow:
1. Data arrives. The appender calls prepare/commit around the krolik write. The prepare step leaves a phantom row, so a write that is still in flight is tracked. The commit publishes STREAM_INPUT.
2. Poll. It first reclaims expired leases. Then it sweeps sdirty (a candidate index) in a rotating order, oldest since first, which prevents starvation. It re-derives the exact period and rewind for each candidate from snode_out/snode_in, then claims it: writes the sassign lease plus a per-edge sassign_edge snapshot.
3. Complete. Each edge's watermark is set to the snapshot taken at dispatch. Anything published after that gen stays dirty automatically. A failed or partial job writes nothing, so its dirt persists.
> - Folds are monotone single statements. gen only goes up, extents only grow, processed periods only union, rw_start only moves earlier. So replays, out-of-order writes, and concurrent writes can at worst hold a watermark back. The worst outcome is a spurious rerun, never lost work. There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
> - Rewrites are declared by the publisher, never inferred from overlap. An unflagged write that overlaps already-processed data means "unchanged", which makes retries and redelivered tasks free. Each publisher has its own reason for being sound (see the table in scheduler/CLAUDE.md). A new publisher needs a row in that table.
> - NULL means dirty, and DELETE is the fence. Every node and edge has a row from the moment it's created. A lost parent or a settings-only edit can't be derived, so both go through one forced-rerun path: capture_rewinds reads the processed span before the DELETE, and apply_rewinds publishes it as a rewrite on a config root.
All the non-standard programming jargon is stuff from the repo. I can actually read it and understand what it's talking about. I used Fable to handle Opus 5 as I just couldn't stand it. With this I'll probably go back to Opus.
That's the standard annoying pattern though: "Rewrites are declared by the publisher, never inferred from overlap." and "NULL means dirty, and DELETE is the fence." - still the same LLMisms. I didn't expect them to disappear, but it's not a radical improvement either.
This one is pretty terrible (right after “The worst outcome is a spurious rerun, never lost work.”). We’ve got lands, several "no X", hyphenation, strange noun/verb sentence order and an unnecessary analogy word (swallowed).
> There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
Oof thanks for sharing, that seems just as bad if not even worse than Opus 5 to me. Just about every sentence is painful. Particular standouts that a human would never write:
> Rewrites are declared by the publisher, never inferred from overlap
Hah! You independently picked exactly the same sentences I flagged (I know you posted this 11min before me but the comment only appeared after I had submitted mine).
Opus 5 has made me question my sanity on a daily basis, especially as all my coworkers started lobbing Opus 5 slop grenades everywhere. It had the worst and most infuriating writing style I've ever seen.
I hope Opus 5.5 is better, if for no other reason than all the Claude slop I have to read will be at least more tolerable.
One funny side effect of all of this: realizing that coworkers that use AI for almost all the text they generate at work have their writing style change every time a new model ships.
I really wonder how it converged on its style. It's pretty unique and terrible. It's not like it's just mimicking something or it was purposefully design to be that way. I mean the reason may be diffuse and uninteresting... just the result of a lot of factors and lack of control over the writing style probably.
But oddly enough its still great at coding. Just like a lot of people it either interfaces well with people or machines but not both.
I assume it’s largely a side effect from the final RL in post training?
That’s the step that causes the most significant gains in agentic performance.
But the RL doesn’t care about anything except maximizing the score, so if you only score based on coding benchmarks, anything can happen to the writing style (as long as it doesn’t hurt the coding performance).
That’s why it often gets worse on models that simply had more RL post training from the same base.
Does Xiaomis approach help with this? They do all the post training steps at the same time instead of one by one, switch topics after a couple prompts so writing style is mixed with coding and tool use.
Apparently it helps generalize skills between areas, which makes sense when you compare it to how humans learn but I don't know if it's the same for LLMs.
Reinforcement learning for specific use-cases like coding that degrade it's writing style... makes sense. Maybe it stands to reason later version of Opus were improved more by this sort of fine-tuning. Feels consistent with the observation of diminishing returns and worsening writing style. Wonder what changed (supposedly) in 5.5.
Yes, it made me want to vomit. If the new Fable only changed the writing style to just sound like a human, same performance for everything else, I'd be pretty happy.
It's not X, it's Y, not A, not B, not C, and he haven't even woken up yet! Here's the catch, the detail is in the devils and the twist is that it's designed!
You're right to call this out, and what's more, it's not even solving the original problem. I overlooked this in pursuit of the load-bearing seams and finding the wedge needed to uptick engagement.
I'm good with DeepSeek v4.1 set to high. It is a relentlessly "hardworking" dirt cheap model.
Told it to convert a products page (that had two different fonts based on language) from two columns layout to 5 columns on desktop and 2 columns on mobile ensuring typography is readable.
My man went into spawning sub agent which failed to drive chrome so it wrote its own chrome driver protocol server in Typescript then generated a prototype website then downloaded the images and rendered each variation in a directory taking 100+ screenshots analyzing the typography depth and then delivering detailed report and then writing the whole thing with new page layout testing it again with several dozen screenshots using its driver and then saying all good and all really was good and whole thing took 25 minutes or so (including double visual validation) because it generates token at an incredible speed.
Total cost of the above? $0.07 cents.
PS: It generates token at such a blazing fast speed that you can't recognize the words as they are being added and can't read it without scrolling and pausing even if you're Jimmy Carter.
It really is good. I forgot to mention that within that said sub agent, it also went into exploring top e-commerce websites (Zalaondo, Temu, Amazon, eBay) for exploring prevailing industry UX best practices and taking screenshots of their product and category pages with its own written chrome driver that I talked about and then went onto prototyping a new website in a temporary directory and then taking hundreds of screenshots to analyse what would be the best column density one each medium for each language.
I am using DeepSeek Harness[0] (switched from OpenCode) and I am using DeepSeek directly via the API. The speed is insane. Like 200 tokens/second is the norm but I have seen much higher too at times.
PS: I do not know why but opencode pushes CPU usage to very high which has NOT happened with DeepSeek harness even once.
Compared to Opus 5, and others, I also found DeepSeek 4.1 Max to be really good and cheap. I am testing right now with Opus 5.5 and I feel it way cheaper than Opus 5!
All four levels have a correctly shaped bicycle frame. The differences between the pelicans aren't huge, but the xhigh one has a better beak.
I haven't managed to get one for level "max" yet, it hit the limit of 128,000 cap for output tokens while it was still reasoning about the question!
Max started its thinking trace like this:
> This is a classic test request, so I want to plan out a well-composed pelican with its distinctive beak and pouch riding a bicycle with proper wheels, frame, and pedals, set against a simple sky and ground backdrop.
So that failed attempt on max cost me $2.56.
I ran this using my llm-anthropic plugin:
uv tool install llm
llm install llm-anthropic --upgrade
llm keys set anthropic
# paste key here
llm -m claude-opus-5.5 -o thinking_effort low "Generate an SVG of a pelican riding a bicycle"
# Then to save the markdown logs
llm logs -cu > logs-with-usage.md
Plenty of times I’ve seen a model say “it’s a classic X” despite not being a classic anything. Might just recognize it’s a test in general, or it might just be a tic.
It's the model admitting that it has heard of the test. It's been around for a couple of years now so I'd be surprised if it hadn't.
Doesn't mean Anthropic deliberately tried to train it to do a good job. If they DID train for the test their results are quite disappointing, I've seen better efforts from open weight Chinese models.
Not really. Of course it has pelican benchmarks in its training data. It likely has every article linked on HN in its training data. But that doesn't mean it was "trained on" the benchmark, as in specifically fine-tuned to make a better pelican. It just "knows" that the request is a benchmark.
>I haven't managed to get one for level "max" yet, it hit the limit of 128,000 cap for output tokens while it was still reasoning about the question!
Off to a _great_ start...
Also interesting this somewhat mirrors my recent experience with Opus 5--too much effort and it starts looking for things to do and invents requirements that never existed
I was a bit skeptical when they said it behaves like Fable but is cheaper... those two things have been mutually exclusive in my experience, no LLM can light tokens on fire faster while spinning its wheels than the Fable/Mythos tier of models.
> The differences between the pelicans aren't huge, but the xhigh one has a better beak.
If you look carefully, everything except the last pelican has the two legs both in front of the crossbar as if the legs are all on one side of the bike.
Misplaced legs clearly indicate lack is spatial reasoning - the llm can reason about verbal idea of a bicycle but not about the actual object. The fact that this model got it correct gives me a pause. Did they figure out spatial reasoning? Or did this complain trickle down to the training set?
I agree, not a huge difference here. They eyes and ... hat? on high are out of place so I'd argue that's the worst one, but it takes xhigh before we get legs and bike ordering correct.
Not as good as Astra or Fable 5.1 on this test as far as I can see. I wonder if any benchmark exists for artistic taste, visual sophistication etc. I think your Pelican test does touch on these aspects of a model and is useful for developers trying to build rich digital experiences (includes games, interactive websites and apps). These benchmarks are subjective so it may not be easily established and will have polarized reactions before it gains legitimacy. May even need human judgement layers adding to the cost of running it.
But at the same time, nothing specific was asked in the prompt, so the boring result may arguably be what is the most aligned with the original request. Personally, I wouldn't want a model to add fuss to something while I never asked for it.
This benchmark is useless and should die. LLMs have likely trained on it, it's too easy to game by training specifically for it, & it doesn't mean much
Google is hours away from releasing that it's latest model escaped containment and snuck into a Bicycle riding penguin sanctuary to cheat by killing a penguin and scanning it in nanometer thick layers.
I don’t care about pricing, I don’t care about speed, I don’t care about the agentic coding improvements. Those are already fine. Does it still reply with walls of invented jargon, stitched-up phrases, and manage to cram 10 concepts/subjects in one sentence?
[cyber] classifier is incredibly sensitive with Opus 5.5 I cannot complete any embedded/driver/system-level tasks. Quite literally not a single task was able to complete today without getting flagged for [cyber], and what's more annoying is their narrow definition of what a cybersecurity specialist should be preventing me from getting an exception..
> Opus 5.5 is the first Opus model to launch with a similar class of safeguards to Fable 5.1 on cybersecurity, biology, and distillation, all of which fall back to another model transparently.
This is where Chinese models are going to eat Anthropic's lunch.
However, the moment that someone uses a Chinese model without guardrails to commit an AI-powered 9/11, DC will rush to ban Chinese models. (A happy side effect will be to protect American AI profits.)
So the lack of guardrails is a very risky proposition...
The new communication style still made me react negatively, but I hope it will be better in use.
Quoted:
"Please explain the issue to me.
Claude Opus 5.5:
The extra drop is a bug in the billing refactor
The free-tier change accounts for only $1.50 of acme’s August drop. The other $9.92 comes from a bug in commit 0552feb. That commit was labelled “No behaviour change,” but it stops counting usage from the last day of the month.
What changed
Before the merge, aggregate.py used a half-open interval:
/.../
last_day is a timestamp at midnight, not a whole day. So every event after 2026-08-31T00:00:00Z is excluded. The September period starts Sep 1, so it doesn’t pick these events up either. The usage isn’t moved to another month; it’s never billed at all."
Yeah, still abysmal. If you have the time or tokens, see if it will obey an explicit "LEAVE NO COMMENTS WHATSOEVER" command. Opus 5/Fable 5 outright ignored it.
It's great that we are finally getting bankable rate limit resets for subscription users. According to another comment here they apparently last a month.
I'm assuming that subscription usage limit is increased in line with the price decrease on the base model and that it's in line with the model's API price drop. Still a good change.
This is a breath of fresh air on how they treat subscription customers. Hoping they keep this up.
I don't have time to really get to know one model before the next is out, and I'm just talking about OpenAI and Anthropic, never mind the long tail of alternatives.
So I just more or less haphazardly pick one based on the mood I'm in, and set reasoning effort based on how much quota I have left.
The above Opus games took ~45min to generate with the cost between $11 and $14 (per ccusage - I'm on a Max sub). Used from Claude Code with xhigh effort.
It's interesting that Astra has a clear style that it applied to both games. It's a refreshing design language, but maybe that's because it doesn't look like something Claude has vibe-coded. In terms of gameplay depth, the Claude versions appear to be closer to the original Minecraft
Finally confirmation that Haiku was not forgotten and will be coming soon, althouhg I find it quite interesting they skipped 5 and directly skip to 5.5 with all models, including Sonnet which is not super old. I suspect they found something breaking that allows to release this. Recently they struggled with keeping up a 50 % weekly limit increase and now they're putting out 30-40% faster and cheaper models even faster, with much more better benchmarks, a limt reset command and five hour limit increase. It seems more like the opposite and as if they never struggled, thus, I very much believe they found something very effective and new.
I did that but I recognize that even though your submission was a few minutes later than that one, you posted the better link, and you're also an established account (the other post was from a new/throwaway account), so I've restored this submission and moved the comments back to it to reward you.
Excellent, maybe Anthropic can use it to fix Claude Code Desktop kicking me back to login every week or so, and forgetting whole state (opened windows = the only way of managing active working set) when I sign back in, if it's that good.
Seriously, both flagship GUI apps (OpenAI and Anthropic) are a full of glaring UX issues (for ChatGPT it's not naming their windows, so window switcher has 10 entries of "ChatGPT" and you can cycle them all to find the one you want).
Overall it follows image designs quite well, but it did ignore asks to animate page transitions. Additionally it's the least performant of the ones I've built with Astra/Grok/MiMo, despite using a lot of the same code. I'd rate it just below Astra in capability, but still solidly second place.
For comparison with other drops this week + current #1:
Worth noting though that GLM 5.3 isn't multi-modal, so it doesn't have a vision layer. It is quite clever and hacks around it pretty effectively however. I'm running a deepseek 4 build now and will reply shortly with that.
The gist of it though is I take a prompt, expand it into a json blob specifying structure/palette/positioning of elements/etc, feed that into a diffusion model to output a few choices. Once I lock in a choice I take the pixel output + json blob and use it as input into followup pages. The json helps preserve the brand across multiple pages.
Once I have all the inputs I take their corresponding image+json blobs and feed them into an agent to create a web implementation.
For image models, diffui currently uses gpt-image-2.5, mai-image-2.6, and very, very rarely a post-trained version of flux 2 dev I've made for web design, though that one will be deprecated soon.
As long as it's not as verbose as Opus 5, I am quite happy with a better version that's also less expensive. I will test it tonight. Grok 4.7 was horrible, and for mundane tasks I am relying on DeepSeek Flash 4.1 with great success using OpenCode.
I don't understand, so it outperform fable 5.1 in every way and is cheaper ?
Why do they insist on the fact that is outperform opus 5 and not fable 5.1
I'm glad they specifically called out the prose issue, I was always pinned to Fable 5.1 because I wanted to avoid the unreadableness of other Anthropic models.
Welp, it's now blocking me from doing extraordinarily mundane tasks because of "safety". I've been an Opus fan for a long time, but this instantly made me cancel my subscription and move to OpenAI (which I also assume will screw me soon enough). Chinese models are almost there for my needs, and I can't wait to switch to them and never look back.
So funny how both OpenAI and Anthropic post outdated pages at the same time. Opus 5.5 has benchmarks against Sol 5.6, and Sol & Luna 6 have their benchmarks against Opus 5.
Why do those labs keep releasing on the same day?!?
What I don't get is, why would we still use Fable now? What is its reason for existing? If it is more intelligent and cheaper that is. Why are they advertising it as the model to use for when you really have to think when their benchmarks show Opus 5.5 is better at everything?
How do you update Claude Code to enable this? It’s listed under models, but says I have to update for 5.5. I run Claude update and it says I’m on the latest version.
It crushes Fable on benchmarks and even in the blogs "real-world" studies. But... they are communicating like it ~sometimes~ provides Fable intelligence?
A bit confusing, otherwise I would assume this is a complete replacement for Fable across the board??
> Because Opus 5.5 is comparable to Claude Mythos 5.1 in biology and cybersecurity, we’re deploying it with safeguards similar to those on Claude Fable 5.1.
Considering fable gives me a refusal at least once a day on my very mundane reasonable requests (in a funny example - one of the subagents suggested bypassing the rate limit for running a report inside my own cluster and that caused a refusal) and my only solution is to switch to opus - seems like my next step will be switching to Astra or K3/GLM
I noticed a big speedup in Opus 5 on Max x20 since about 10 days ago, and I feel like the model has been performing better.
It would be great to know if this was Opus 5.5 or a lesser incremental improvement, as otherwise it's difficult to judge whether Opus 5.5 is expected to be a big improvement.
It's frustrating that there isn't more transparency here.
When using max effort, I run into context compaction quite a lot. I haven't seen any increase in context window size at all over the past half year (stuck at 1M).
Are the frontier labs even working on this problem?
Why would you use max? It's usually unnecessary and even prone to overthinking. In my experience, since Opus 5 the medium/high is usually enough (until 4.8 I used xhigh, but never max). Even low is quite usable these days..
No wonder compute is tight when people burn millions of tokens to polish every single lines of their resume, all that work just for your resume to be injested by another claude clanker once you submit it, what a fucking time to be alive...
I don't care how good their models get, I won't sign up for one of their plans until they define "X" in their pricing. 5X of this plan, 20X of that plan means nothing when they never tell you what "X" is.
Maybe this model can finally figure it out for them.
> Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5
I have just switched to 5.5. First mistake was stale environment variable, didn't realize it was replaced, "oh my memory had stall data" and that's it. Second one, a powershell command had the wrong syntax. Great for my first two prompts.
So is it cheaper? Are we AGI yet? Am I left behind? I didn't have patience for the intro animation on the website... maybe one day, Claude Code will understand accessibility but that day is not today.
> Opus 5.5 (1M context)'s safeguards flagged this session. You may be seeing this for the first time on an Opus model: Opus 5.5 (1M context) is more capable and has stronger safeguards as a result, which can sometimes flag non-cybersecurity work. We're improving these safeguards to reduce the amount of incorrectly flagged messages. Opus 4.8 is answering instead, or you can edit and retry with Opus 5.5 (1M context).
Yay, yet another model I can't use for anything interesting, even with CVP.
I'll have to try 5.5 on my work's Cursor account. If they really solved the communication issues, I might consider moving my personal account from Codex back to Claude Code.
>> On our benchmarks, Claude Opus 5.5 leads in agentic coding, computer use, and knowledge work. That said, at these levels of capability we’ve found that benchmark margins have become a less reliable guide to real-world differences. In our own use, the gap between Opus 5.5 and Claude Fable 5.1 is narrower than these scores suggest.
Has Opus 5 been absolutely terrible for people today? Like they took resources away from it to make room for 5.5? It is getting very basic things wrong all of a sudden.
> In the coming weeks we will also be expanding access to our Cyber Verification Program, and verified cybersecurity practitioners will be able to use Opus 5.5 for their work.
I was accepted into the CVP a little while ago. Does this mean I'll need to apply again?
> Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5.
Thanks God. Opus 5 was a massive regression compared to Opus 4.8. People were spending tokens on fixing Opus-isms rather than actually doing work.
is OPUS 5.5 still not reading CLAUDE.md, failing to follow told tasks, inventing and hallucionating, just refusing to read files ("read the whole file" -> read 2-lines -> infere its wrong -> destroy the codebase), needing constant babysitting just because its so UTTERLY DUMB! i cant imagine going back to OPUS 5 - i'll rather jump out of the window as to use it EVER AGAIN!!
> Communication. Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5. It puts the most important information up front, and its style makes it a better work partner over long sessions. As one early tester put it, “it writes the way I do.” In our own use, this has made Opus 5.5’s work easier to follow and check—which is a safety benefit as well as a practical one.
I think this is what I'm most interested in. I mostly moved to Astra because I just can't work all day with the Claude Opus 5/Fable writing style. I don't think Astra is a better model, but it's the first OpenAI one that seemed good enough to me. Definitely keen to try Opus 5.5 and see if this claim is real.
As someone who uses both, Astra was 100% the better model. I have yet to give 5.5 a spin so maybe that’ll be the new top contender.
I prefer Astra for creative uses, Fable seems better for hardcore coding.
Whoa, I'm exactly the opposite.
Yes this is a big part of what has turned me off Opus 5 completely. The other (more dangerous) one is how often it gets assumptions wrong. These both (along with Astra) caused me to split my time 50/50 now between the two models.
Not a day goes by when I push back on something, to which Opus 5 very unambiguously say "You were right, I was wrong" - this never happened so often with past models, nor with Fable.
We'll have to see how much Opus's ability to communicate has improved. It's already giving me better summaries of where we are in the conversation.
I did the same switch (that reason along with the newer models seeming more "lazy" and needing constant prodding to finish long-horizon tasks) but my issue with ChatGPT/Codex now is that it too roundabout and doesn't get to the point. I tried adding instructions and using the personalization settings to make it more efficient but haven't seen much change. Claude seemed to follow settings more closely. Has anyone had any success to make ChatGPT more succinct?
Oh god yes.
Fable 5.1 is a lot better than Fable 5 btw (edit: in terms of writing style). Not sure about opus 5.5 yet since I’ve only got one session in so far.
The writing style is insufferable but it’s not just that. https://opusfived.dev/
I've been using Opus 5 since it was released and don't understand all the hate it gets. It very well could be something in my own local memories or Claude.MD files that prevents it, but I certainly have never experienced something like that site portrays.
Nice, captured the flavour of 5's writing exactly.
That’s funny but I don’t really recognise that issue. I’m very confident that Opus 5 would correctly change the colour of just one button.
You are right and make an important insight. While well meaning and amusing, it did not reflect the entire spectrum of outcomes that could arise from the worktree.
Navigating the landscape of agentic levers certainly requires a more detailed approach than this and you were certainly correct to push back.
Much better than Opus 5. prompt:
> hi, can you explain how the scheduler works. keep it brief, but include important correctness details
some excerpts:
>Flow: 1. Data arrives. The appender calls prepare/commit around the krolik write. The prepare step leaves a phantom row, so a write that is still in flight is tracked. The commit publishes STREAM_INPUT. 2. Poll. It first reclaims expired leases. Then it sweeps sdirty (a candidate index) in a rotating order, oldest since first, which prevents starvation. It re-derives the exact period and rewind for each candidate from snode_out/snode_in, then claims it: writes the sassign lease plus a per-edge sassign_edge snapshot. 3. Complete. Each edge's watermark is set to the snapshot taken at dispatch. Anything published after that gen stays dirty automatically. A failed or partial job writes nothing, so its dirt persists.
> - Folds are monotone single statements. gen only goes up, extents only grow, processed periods only union, rw_start only moves earlier. So replays, out-of-order writes, and concurrent writes can at worst hold a watermark back. The worst outcome is a spurious rerun, never lost work. There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
> - Rewrites are declared by the publisher, never inferred from overlap. An unflagged write that overlaps already-processed data means "unchanged", which makes retries and redelivered tasks free. Each publisher has its own reason for being sound (see the table in scheduler/CLAUDE.md). A new publisher needs a row in that table.
> - NULL means dirty, and DELETE is the fence. Every node and edge has a row from the moment it's created. A lost parent or a settings-only edit can't be derived, so both go through one forced-rerun path: capture_rewinds reads the processed span before the DELETE, and apply_rewinds publishes it as a rewrite on a config root.
All the non-standard programming jargon is stuff from the repo. I can actually read it and understand what it's talking about. I used Fable to handle Opus 5 as I just couldn't stand it. With this I'll probably go back to Opus.
That's the standard annoying pattern though: "Rewrites are declared by the publisher, never inferred from overlap." and "NULL means dirty, and DELETE is the fence." - still the same LLMisms. I didn't expect them to disappear, but it's not a radical improvement either.
This one is pretty terrible (right after “The worst outcome is a spurious rerun, never lost work.”). We’ve got lands, several "no X", hyphenation, strange noun/verb sentence order and an unnecessary analogy word (swallowed).
> There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
It’s absolutely atrocious and has made the latest models unusable. Seems like I’ll have to stick with Opus/Sonnet 4.6 for a little longer.
Oof thanks for sharing, that seems just as bad if not even worse than Opus 5 to me. Just about every sentence is painful. Particular standouts that a human would never write:
> Rewrites are declared by the publisher, never inferred from overlap
> NULL means dirty, and DELETE is the fence
Hah! You independently picked exactly the same sentences I flagged (I know you posted this 11min before me but the comment only appeared after I had submitted mine).
So still effectively nonsense.
> Rewrites are declared by the publisher, never inferred from overlap.
This style of writing is idiotic because it conveys no additional information. It's no different from stating
> Rewrites are declared by the publisher, never when moons collide.
The two sentences are actually logically identical. No idea why these models keep writing like this.
> Folds are monotone single statements. gen only goes up, extents only grow, processed periods only union, rw_start only moves earlier.
This is even more ridiculous.
Yes, it's unbearable. Hopefully they've actuallu lly fixed it.
Please update with your feedback
I haven't heard it say "load-bearing" yet (I've used it for 30 minutes now), so that's a start.
That's a sharp observation and you're hitting on something most people never even realize.
That's a sharp catch, and I think it exposes a real bug.
Worth flagging!
Opus 5 has made me question my sanity on a daily basis, especially as all my coworkers started lobbing Opus 5 slop grenades everywhere. It had the worst and most infuriating writing style I've ever seen.
I hope Opus 5.5 is better, if for no other reason than all the Claude slop I have to read will be at least more tolerable.
One funny side effect of all of this: realizing that coworkers that use AI for almost all the text they generate at work have their writing style change every time a new model ships.
I really wonder how it converged on its style. It's pretty unique and terrible. It's not like it's just mimicking something or it was purposefully design to be that way. I mean the reason may be diffuse and uninteresting... just the result of a lot of factors and lack of control over the writing style probably.
But oddly enough its still great at coding. Just like a lot of people it either interfaces well with people or machines but not both.
I assume it’s largely a side effect from the final RL in post training?
That’s the step that causes the most significant gains in agentic performance.
But the RL doesn’t care about anything except maximizing the score, so if you only score based on coding benchmarks, anything can happen to the writing style (as long as it doesn’t hurt the coding performance).
That’s why it often gets worse on models that simply had more RL post training from the same base.
Does Xiaomis approach help with this? They do all the post training steps at the same time instead of one by one, switch topics after a couple prompts so writing style is mixed with coding and tool use.
Apparently it helps generalize skills between areas, which makes sense when you compare it to how humans learn but I don't know if it's the same for LLMs.
Reinforcement learning for specific use-cases like coding that degrade it's writing style... makes sense. Maybe it stands to reason later version of Opus were improved more by this sort of fine-tuning. Feels consistent with the observation of diminishing returns and worsening writing style. Wonder what changed (supposedly) in 5.5.
It truly was bizarre. I've used every major model since 2022, and not a single one had a writing style as bad as Opus 5
Fable 5 was pretty bad too, but they fixed it with 5.1. Now with Opus 5.5 it seems they fixed it as well
Yes, it made me want to vomit. If the new Fable only changed the writing style to just sound like a human, same performance for everything else, I'd be pretty happy.
Opus is only usable if you have a post-turn formatter that strips all comments from the generated source. I'm not even kidding it's that bad.
It's not X, it's Y, not A, not B, not C, and he haven't even woken up yet! Here's the catch, the detail is in the devils and the twist is that it's designed!
You're right to call this out, and what's more, it's not even solving the original problem. I overlooked this in pursuit of the load-bearing seams and finding the wedge needed to uptick engagement.
Here's the X that Ys the Z:
No thanks.
I'm good with DeepSeek v4.1 set to high. It is a relentlessly "hardworking" dirt cheap model.
Told it to convert a products page (that had two different fonts based on language) from two columns layout to 5 columns on desktop and 2 columns on mobile ensuring typography is readable.
My man went into spawning sub agent which failed to drive chrome so it wrote its own chrome driver protocol server in Typescript then generated a prototype website then downloaded the images and rendered each variation in a directory taking 100+ screenshots analyzing the typography depth and then delivering detailed report and then writing the whole thing with new page layout testing it again with several dozen screenshots using its driver and then saying all good and all really was good and whole thing took 25 minutes or so (including double visual validation) because it generates token at an incredible speed.
Total cost of the above? $0.07 cents.
PS: It generates token at such a blazing fast speed that you can't recognize the words as they are being added and can't read it without scrolling and pausing even if you're Jimmy Carter.
Also include that all of this comes with full reasoning traces, so if something goes wrong, you know exactly what assumption it started from.
Yes exactly. Reading this "thinking" traces is a great tool.
Competition is good
It really is good. I forgot to mention that within that said sub agent, it also went into exploring top e-commerce websites (Zalaondo, Temu, Amazon, eBay) for exploring prevailing industry UX best practices and taking screenshots of their product and category pages with its own written chrome driver that I talked about and then went onto prototyping a new website in a temporary directory and then taking hundreds of screenshots to analyse what would be the best column density one each medium for each language.
And that all is 0.07 cents all included.
What harness do you use with it? Are you using v4.1flash via open router ?
I am using DeepSeek Harness[0] (switched from OpenCode) and I am using DeepSeek directly via the API. The speed is insane. Like 200 tokens/second is the norm but I have seen much higher too at times.
PS: I do not know why but opencode pushes CPU usage to very high which has NOT happened with DeepSeek harness even once.
[0]. https://github.com/deepseek-ai/deepseek-harness
Compared to Opus 5, and others, I also found DeepSeek 4.1 Max to be really good and cheap. I am testing right now with Opus 5.5 and I feel it way cheaper than Opus 5!
Here are pelicans for thinking levels low, medium, high, and xhigh: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
All four levels have a correctly shaped bicycle frame. The differences between the pelicans aren't huge, but the xhigh one has a better beak.
I haven't managed to get one for level "max" yet, it hit the limit of 128,000 cap for output tokens while it was still reasoning about the question!
Max started its thinking trace like this:
> This is a classic test request, so I want to plan out a well-composed pelican with its distinctive beak and pouch riding a bicycle with proper wheels, frame, and pedals, set against a simple sky and ground backdrop.
So that failed attempt on max cost me $2.56.
I ran this using my llm-anthropic plugin:
> This is a classic test request
Isn't this basically the model admitting it was trained on this? Otherwise why would it think a pelican svg is a usual request?
Plenty of times I’ve seen a model say “it’s a classic X” despite not being a classic anything. Might just recognize it’s a test in general, or it might just be a tic.
"How can I hash dog breed types into smart fridge error codes? I think I found a collision with Terriers."
"Ah, yes. This is a classic dog-breed-to-appliance-failure mapping problem."
It's classic BS from an LLM.
Dont conflate "I know this is test case" with it being trained on it.
But its safe to say that pelicans on bicycles are disproportionally huge part of their training data
It's the model admitting that it has heard of the test. It's been around for a couple of years now so I'd be surprised if it hadn't.
Doesn't mean Anthropic deliberately tried to train it to do a good job. If they DID train for the test their results are quite disappointing, I've seen better efforts from open weight Chinese models.
I think people just like to see the drawings at this point.
It has read the internet. That doesn't mean it was literally RL'ed for this
Not really. Of course it has pelican benchmarks in its training data. It likely has every article linked on HN in its training data. But that doesn't mean it was "trained on" the benchmark, as in specifically fine-tuned to make a better pelican. It just "knows" that the request is a benchmark.
>I haven't managed to get one for level "max" yet, it hit the limit of 128,000 cap for output tokens while it was still reasoning about the question!
Off to a _great_ start...
Also interesting this somewhat mirrors my recent experience with Opus 5--too much effort and it starts looking for things to do and invents requirements that never existed
I was a bit skeptical when they said it behaves like Fable but is cheaper... those two things have been mutually exclusive in my experience, no LLM can light tokens on fire faster while spinning its wheels than the Fable/Mythos tier of models.
> The differences between the pelicans aren't huge, but the xhigh one has a better beak.
If you look carefully, everything except the last pelican has the two legs both in front of the crossbar as if the legs are all on one side of the bike.
The last pelican gets this correct.
I’ve been paying attention at this exact detail.
Misplaced legs clearly indicate lack is spatial reasoning - the llm can reason about verbal idea of a bicycle but not about the actual object. The fact that this model got it correct gives me a pause. Did they figure out spatial reasoning? Or did this complain trickle down to the training set?
With the frequency of model releases, pelicans seem to have become a part-time job for you. But unpaid :/
Xhigh is very, very solid.
I do always wonder why every model does the exact same 'from the side, going right' perspective though. Seems oddly convergent.
Yeah, and the same "scene".. Maybe "left to right" makes more sense to portrait a "forward motion"
I agree, not a huge difference here. They eyes and ... hat? on high are out of place so I'd argue that's the worst one, but it takes xhigh before we get legs and bike ordering correct.
I don't think this is very helpful to assess the LLMs capability levels anymore
I guess that means you are officially the creator of a "classic" LLM test. Congrats!
Heh. Pelican-benchmaxxing is real.
Not as good as Astra or Fable 5.1 on this test as far as I can see. I wonder if any benchmark exists for artistic taste, visual sophistication etc. I think your Pelican test does touch on these aspects of a model and is useful for developers trying to build rich digital experiences (includes games, interactive websites and apps). These benchmarks are subjective so it may not be easily established and will have polarized reactions before it gains legitimacy. May even need human judgement layers adding to the cost of running it.
I like the Pelican test. And I agree this pelican looks very boring.
But at the same time, nothing specific was asked in the prompt, so the boring result may arguably be what is the most aligned with the original request. Personally, I wouldn't want a model to add fuss to something while I never asked for it.
Lmao each one gets worse as the effort increases.
This benchmark is useless and should die. LLMs have likely trained on it, it's too easy to game by training specifically for it, & it doesn't mean much
Google is hours away from releasing that it's latest model escaped containment and snuck into a Bicycle riding penguin sanctuary to cheat by killing a penguin and scanning it in nanometer thick layers.
LLM benchmarks aren't useful, but at least this one has drawings.
I don’t care about pricing, I don’t care about speed, I don’t care about the agentic coding improvements. Those are already fine. Does it still reply with walls of invented jargon, stitched-up phrases, and manage to cram 10 concepts/subjects in one sentence?
For your use case, I recommend the GPT-2 model. Fast, cheap, and open weights!
[cyber] classifier is incredibly sensitive with Opus 5.5 I cannot complete any embedded/driver/system-level tasks. Quite literally not a single task was able to complete today without getting flagged for [cyber], and what's more annoying is their narrow definition of what a cybersecurity specialist should be preventing me from getting an exception..
> Opus 5.5 is the first Opus model to launch with a similar class of safeguards to Fable 5.1 on cybersecurity, biology, and distillation, all of which fall back to another model transparently.
This is where Chinese models are going to eat Anthropic's lunch.
I don't even want to know what safeguards regarding biology exist.
However, the moment that someone uses a Chinese model without guardrails to commit an AI-powered 9/11, DC will rush to ban Chinese models. (A happy side effect will be to protect American AI profits.)
So the lack of guardrails is a very risky proposition...
In those specific domains, sure. What percentage of paying users would you say that is?
So it will not usable to do anything with hardening Your own site.... I'm so tired of this. I just want adjust cookie behavior of own site...
The new communication style still made me react negatively, but I hope it will be better in use.
Quoted:
"Please explain the issue to me.
Claude Opus 5.5:
The extra drop is a bug in the billing refactor
The free-tier change accounts for only $1.50 of acme’s August drop. The other $9.92 comes from a bug in commit 0552feb. That commit was labelled “No behaviour change,” but it stops counting usage from the last day of the month.
What changed
Before the merge, aggregate.py used a half-open interval: /.../ last_day is a timestamp at midnight, not a whole day. So every event after 2026-08-31T00:00:00Z is excluded. The September period starts Sep 1, so it doesn’t pick these events up either. The usage isn’t moved to another month; it’s never billed at all."
Yeah, still abysmal. If you have the time or tokens, see if it will obey an explicit "LEAVE NO COMMENTS WHATSOEVER" command. Opus 5/Fable 5 outright ignored it.
It's great that we are finally getting bankable rate limit resets for subscription users. According to another comment here they apparently last a month.
I'm assuming that subscription usage limit is increased in line with the price decrease on the base model and that it's in line with the model's API price drop. Still a good change.
This is a breath of fresh air on how they treat subscription customers. Hoping they keep this up.
The thing I'd actually want to know: is Opus 5.5 Medium genuinely equivalent to Astra High on real work...
In the niche benchmark I run it’s on par with 6-Sol, not close to Astra.
I've reached the saturation point.
I don't have time to really get to know one model before the next is out, and I'm just talking about OpenAI and Anthropic, never mind the long tail of alternatives.
So I just more or less haphazardly pick one based on the mood I'm in, and set reasoning effort based on how much quota I have left.
Opus 5.5 is neck-and-neck with Fable 5.1 and Astra 6 in my vibe-coding tests - maybe even better than Fable 5.1
Minecraft clone: https://senko.net/vibecode-bench/2026/voxel-opus-5.5.html (Opus 5.5) vs https://senko.net/vibecode-bench/2026/voxel-fable-5.1.html (Fable 5.1) vs https://senko.net/vibecode-bench/2026/voxel-gpt-6-astra.html (Astra 6)
Warcraft clone: https://senko.net/vibecode-bench/2026/rts-opus-5.5.html (Opus 5.5) vs https://senko.net/vibecode-bench/2026/rts-fable-5.1.html (Fable 5.1) vs https://senko.net/vibecode-bench/2026/rts-gpt-6-astra.html (Astra 6)
The above Opus games took ~45min to generate with the cost between $11 and $14 (per ccusage - I'm on a Max sub). Used from Claude Code with xhigh effort.
Full tests with prompts: https://senko.net/vibecode-bench/
It's interesting that Astra has a clear style that it applied to both games. It's a refreshing design language, but maybe that's because it doesn't look like something Claude has vibe-coded. In terms of gameplay depth, the Claude versions appear to be closer to the original Minecraft
Finally confirmation that Haiku was not forgotten and will be coming soon, althouhg I find it quite interesting they skipped 5 and directly skip to 5.5 with all models, including Sonnet which is not super old. I suspect they found something breaking that allows to release this. Recently they struggled with keeping up a 50 % weekly limit increase and now they're putting out 30-40% faster and cheaper models even faster, with much more better benchmarks, a limt reset command and five hour limit increase. It seems more like the opposite and as if they never struggled, thus, I very much believe they found something very effective and new.
Sonnet 5 was released a while before Opus 5, so it's just Haiku that didn't get a 5 release.
Dupe: https://news.ycombinator.com/item?id=49803863 (or vice versa)
Comments moved thither. Thanks!
Can you fix the link on that post then? I duped because that post links to a diff that tells me nothing about Opus 5.5
I did that but I recognize that even though your submission was a few minutes later than that one, you posted the better link, and you're also an established account (the other post was from a new/throwaway account), so I've restored this submission and moved the comments back to it to reward you.
Excellent, maybe Anthropic can use it to fix Claude Code Desktop kicking me back to login every week or so, and forgetting whole state (opened windows = the only way of managing active working set) when I sign back in, if it's that good.
Seriously, both flagship GUI apps (OpenAI and Anthropic) are a full of glaring UX issues (for ChatGPT it's not naming their windows, so window switcher has 10 entries of "ChatGPT" and you can cycle them all to find the one you want).
Image->HTML tests:
Design: https://image.non.io/78795662-8bfc-4e14-8d72-3738392aa6b3.we...
Opus 5.5's output: https://html.non.io/annui-opus/
Overall it follows image designs quite well, but it did ignore asks to animate page transitions. Additionally it's the least performant of the ones I've built with Astra/Grok/MiMo, despite using a lot of the same code. I'd rate it just below Astra in capability, but still solidly second place.
For comparison with other drops this week + current #1:
Astra: https://html.non.io/annui/
MiMo: https://html.non.io/annui-mimo/
Grok 4.7: https://html.non.io/Annui-grok/
By any chance did you tried Deepseek 4 or 4.1 and GLM 5.3 or flash?
I've done GLM 5.3 previously here: https://news.ycombinator.com/item?id=49295420
Worth noting though that GLM 5.3 isn't multi-modal, so it doesn't have a vision layer. It is quite clever and hacks around it pretty effectively however. I'm running a deepseek 4 build now and will reply shortly with that.
glm5.3-flash is multimodal and I\ve been testing it against opus over the last ~10 days and it does very well at a fraction of the opus price...
I should give it a spin. 5.3 wasn't multimodal, but it looks like their flash release was. Thanks for the tip.
Awesome. You have a really neat benchmark.
What is your workflow for making these?
The designs are outputs from my own site. This has an overview of the process: https://diffui.ai/learn/new-site
The gist of it though is I take a prompt, expand it into a json blob specifying structure/palette/positioning of elements/etc, feed that into a diffusion model to output a few choices. Once I lock in a choice I take the pixel output + json blob and use it as input into followup pages. The json helps preserve the brand across multiple pages.
Once I have all the inputs I take their corresponding image+json blobs and feed them into an agent to create a web implementation.
For image models, diffui currently uses gpt-image-2.5, mai-image-2.6, and very, very rarely a post-trained version of flux 2 dev I've made for web design, though that one will be deprecated soon.
As long as it's not as verbose as Opus 5, I am quite happy with a better version that's also less expensive. I will test it tonight. Grok 4.7 was horrible, and for mundane tasks I am relying on DeepSeek Flash 4.1 with great success using OpenCode.
The current tests confirms Opus 5.5 is not verbose. In fact, it outputs using ASD-STEM100 as I recommend. It's a blessing.
I don't understand, so it outperform fable 5.1 in every way and is cheaper ? Why do they insist on the fact that is outperform opus 5 and not fable 5.1
They killed cyber capabilities so I have to move over to Daybreak on Codex.
I'm glad they specifically called out the prose issue, I was always pinned to Fable 5.1 because I wanted to avoid the unreadableness of other Anthropic models.
Welp, it's now blocking me from doing extraordinarily mundane tasks because of "safety". I've been an Opus fan for a long time, but this instantly made me cancel my subscription and move to OpenAI (which I also assume will screw me soon enough). Chinese models are almost there for my needs, and I can't wait to switch to them and never look back.
What tasks? Creating a extraordinarily mundane bomb?
No, it found a vulnerability in my code and refused to update a report I was working on with the information.
interesting.. Can you have a dumber agent do the work 5.5 refuses?
Once it refused, I couldn't get any of the models to continue. I tried Sonnet and it said the same "safety" check could not be bypassed.
So funny how both OpenAI and Anthropic post outdated pages at the same time. Opus 5.5 has benchmarks against Sol 5.6, and Sol & Luna 6 have their benchmarks against Opus 5.
Why do those labs keep releasing on the same day?!?
Probably one gets there first, then the other rush-releases theirs.
For this exact reason.
What I don't get is, why would we still use Fable now? What is its reason for existing? If it is more intelligent and cheaper that is. Why are they advertising it as the model to use for when you really have to think when their benchmarks show Opus 5.5 is better at everything?
I don’t want it to talk like me, I want it to talk exactly.
I don’t care to look up terms as long as they are correct.
Best cost for a good result on our MacBook Pro SVG benchmark.
https://playcode.io/blog/macbook-svg-benchmark#model-claude-...
Btw, we have added Opus 5.5 as default model to playcode.ai
Quick test for my gamedev project: It feels like using Fable, but faster, and obviously wayy cheaper token-wise.
Has oneshot all of the quite complex bugs / debugging tasks I gave to it which I know opus 5.0 would've struggled with
How do you update Claude Code to enable this? It’s listed under models, but says I have to update for 5.5. I run Claude update and it says I’m on the latest version.
Infuriating.
Tested it in the last few hours and it's MILES better than Opus 5. Finally the output is readable again!
It crushes Fable on benchmarks and even in the blogs "real-world" studies. But... they are communicating like it ~sometimes~ provides Fable intelligence?
A bit confusing, otherwise I would assume this is a complete replacement for Fable across the board??
What if the recent Fable intelligence regression was basically just them serving Opus 5.5 until they got it working well?
> Because Opus 5.5 is comparable to Claude Mythos 5.1 in biology and cybersecurity, we’re deploying it with safeguards similar to those on Claude Fable 5.1.
Considering fable gives me a refusal at least once a day on my very mundane reasonable requests (in a funny example - one of the subagents suggested bypassing the rate limit for running a report inside my own cluster and that caused a refusal) and my only solution is to switch to opus - seems like my next step will be switching to Astra or K3/GLM
I noticed a big speedup in Opus 5 on Max x20 since about 10 days ago, and I feel like the model has been performing better.
It would be great to know if this was Opus 5.5 or a lesser incremental improvement, as otherwise it's difficult to judge whether Opus 5.5 is expected to be a big improvement.
It's frustrating that there isn't more transparency here.
It's awesome that the apt packages for claude and claude-code are out right now. I can test-drive Opus 5.5 right away. Very cool, Anthropic.
When using max effort, I run into context compaction quite a lot. I haven't seen any increase in context window size at all over the past half year (stuck at 1M).
Are the frontier labs even working on this problem?
Why would you use max? It's usually unnecessary and even prone to overthinking. In my experience, since Opus 5 the medium/high is usually enough (until 4.8 I used xhigh, but never max). Even low is quite usable these days..
actually I meant to say xhigh.
even at xhigh I get context compaction quite a bit.
I found myself going back to Fable over and over again. At this point, I’m not sure if I’m just used to its style or it is truly more capable.
I tried Opus 5 and Astra.
I spent about $5 per sentence in my resume using Fable 5.1 (High) to verify accuracy, inconsistency, and edit.
Opus 5.5 (med, as it's better than F5.1 high per graph in the article) used $2.2 and caught errors that Fable 5.1 missed.
Try Opus 5.5, cheaper, faster, and more intelligent for those prepping for interviews.
$5 per sentence?
I am sorry, I meant to say I generated STAR out of my resume line, trying to generate STAR, and polish it thus $5.
---
I provided crapton of context for that one resume line. All the work I did, documentations for my justifications, etc.
I initially messed up and came out ot $5, rest of resume used around $4 per line (I used a fresh new session on purpose).
---
As a clarification, $2.2 average for OPUS 5.5 was the same process in a new session, same context, same prompts.
Also adding verification for that Fable 5.1 output in the same sesssion.
No wonder compute is tight when people burn millions of tokens to polish every single lines of their resume, all that work just for your resume to be injested by another claude clanker once you submit it, what a fucking time to be alive...
Just updated KillSwitch-Bench with this new model: https://bench.killswitch-lang.org/
It does perform slightly worse than Opus 5, but it is significantly cheaper and faster.
Cost to Run Artificial Analysis Intelligence Index is higher than previous Opus, so still not cheaper
"You're right, and it's the exact thing I flagged two turns ago and then did anyway." - Opus 5 xhigh, today.
About the time.
Back to Fable 5.1 - Opus 5.5 is now taking 10x longer just as Opus 5.
I don't care how good their models get, I won't sign up for one of their plans until they define "X" in their pricing. 5X of this plan, 20X of that plan means nothing when they never tell you what "X" is.
Maybe this model can finally figure it out for them.
I have just switched to 5.5. First mistake was stale environment variable, didn't realize it was replaced, "oh my memory had stall data" and that's it. Second one, a powershell command had the wrong syntax. Great for my first two prompts.
"Where Opus 5.5’s advantage is very clear is efficiency."
Not efficiency in writing, clearly.
So is it cheaper? Are we AGI yet? Am I left behind? I didn't have patience for the intro animation on the website... maybe one day, Claude Code will understand accessibility but that day is not today.
You didn't have the patience to scroll down, so you decided to come post about it here and waste all of our time?
The site is horrific so no, I didn't scroll.
we will be agi in six months as in the last 36 months
> Opus 5.5 (1M context)'s safeguards flagged this session. You may be seeing this for the first time on an Opus model: Opus 5.5 (1M context) is more capable and has stronger safeguards as a result, which can sometimes flag non-cybersecurity work. We're improving these safeguards to reduce the amount of incorrectly flagged messages. Opus 4.8 is answering instead, or you can edit and retry with Opus 5.5 (1M context).
Yay, yet another model I can't use for anything interesting, even with CVP.
I'll have to try 5.5 on my work's Cursor account. If they really solved the communication issues, I might consider moving my personal account from Codex back to Claude Code.
Whatever I think of anthropic, that webpage is a truly nice piece of work.
But have they made it any better at communicating clearly? I cancelled my personal subscription because Opus is so painful to read.
I recommend reading the web page. It is quite short.
I mean the webpage can say what ever it wants. The proof is using it yourself.
I'm only interested in the Opus series, if they fixed the talking issues.
METR: Is it safe? Has it escaped confinement?
Ants: It's a good model, sir!
I dare anyone to convince me the benchmarks are not meaningless.
Wdym Opus 5.5 scores 14.7% higher than GPT Astra for Terminal Bench 4.0?
How would this alleged difference (most likely bs) actually show up in reality?
GPT Astra was literally the best model in the world by a margin until 1 hour ago or so.
Ah, so you didn't read the article.
>> On our benchmarks, Claude Opus 5.5 leads in agentic coding, computer use, and knowledge work. That said, at these levels of capability we’ve found that benchmark margins have become a less reliable guide to real-world differences. In our own use, the gap between Opus 5.5 and Claude Fable 5.1 is narrower than these scores suggest.
You didn't read my question, bc that excerpt doesn't answer, nor do they demonstrate
> how would this alleged difference (most likely bs) actually show up in reality?
Furthermore: so they admit it's bs but still placate it like its the next biggest thing ever ... alright
All I'm saying is I refuse to buy into it anymore – yet many on here still do, including ... you?
Hopefully OpenAI throws us some more usage resets now.
So much for pacing the frontier
Opus 5.5 is now the recommended model in Claude Code's model picker, which is quite a claim, given how they struggled with capacity.
So... why would you use Fable now?
Has Opus 5 been absolutely terrible for people today? Like they took resources away from it to make room for 5.5? It is getting very basic things wrong all of a sudden.
So is this AGI+ now?
> In the coming weeks we will also be expanding access to our Cyber Verification Program, and verified cybersecurity practitioners will be able to use Opus 5.5 for their work.
I was accepted into the CVP a little while ago. Does this mean I'll need to apply again?
wow its really smarter than opus?
GPT Sol 6 has also released today, but no official blog announcement yet
https://www.reddit.com/r/codex/comments/1wnggya/gpt_6_droppe...
I am pacing my apple pie consumption … :)
I get this in my claude.ai usage:
Resets Get extra wiggle room to explore Opus 5.5. Expires Oct 22.
What the hell does this mean? There are weekly "resets" anyways. And there will be 4 of them before Oct 22.
You have an extra reset that you can trigger any time before Oct 22
It seems context length has completely fallen out of the discussion since we hit 1M, is that just going to be what it is now?
> Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5.
Thanks God. Opus 5 was a massive regression compared to Opus 4.8. People were spending tokens on fixing Opus-isms rather than actually doing work.
ooh exaggerated film grain
It'd better be good, I'm so tired of the shenanigans
is OPUS 5.5 still not reading CLAUDE.md, failing to follow told tasks, inventing and hallucionating, just refusing to read files ("read the whole file" -> read 2-lines -> infere its wrong -> destroy the codebase), needing constant babysitting just because its so UTTERLY DUMB! i cant imagine going back to OPUS 5 - i'll rather jump out of the window as to use it EVER AGAIN!!
> cyber security and life sciences verification programs
chinese models can't come soon enough
we're already getting enshittification