Interesting how the very first line is used to remind the reader of their call to pace the frontier just last week, and everything else after that line is to demonstrate with very specific numbers how they absolutely are not pacing.
Edit: In response to the initial replies. To me it clearly means "releasing frontier models at any pace less than as fast as possible". It implies relative restraint compared to the previous state and without stating the degree of restraint.
I'm on the fence about calling out AI-isms but I think it's definitely worthwhile to call out ones that actually don't make sense.
Is this the meaning or do I have it wrong? I have not checked.
but without using the word "regulate" which is a negative connotation to business
but a "pacer" would be a leader of a pack which is a positive spin
it's classical business marketing language silliness
To pace something is a fairly regular formulation in racing, running, cycling, most sports. You can "pace yourself to reach the festival by bike in about three hours to not gas out". This means to control your speed and time investment intentionally so you don't run out of energy or steam and run into leg cramps before your goal.
But I have noted a point to simplify my vocabulary at work to optimize the audience capable of understanding. So I rather defer the delving into deep dark corners of the dictionary derived from devouring literature to a simple intro or outro, and people find it funny, especially if the rest is easy to read. Claude on the other hand does not do that.
A world exists beyond your vocabulary, post it. Apparently, quite a big world.
Wtf is the meaning? Means absolutely nothing to me having not seen the apparent announcement last week introducing the obscure term.
Imho people should just respond to actual ideas instead of constantly engaging in the second-order critique of how the language may or may not have been created.
It strikes me as the intellectual equivalent of "gossip" to be constantly engaging in second-order commentary on words. Of course gossip has its place and purpose, but if we seem to only let our minds live at that level, we're not moving between all the required scales of thinking that are required of this moment imho <3
Personally I consider it equally valid for people to publicly express annoyance with somebody's choice of words and for everybody to completely ignore that annoyance.
sir, this is a hacker news thread
They’re limiting frontier model development speed. Others are too. Pacing is the only word here to criticize, and I think it’s fine given the limiting of speed but also increased oversight. I’m not saying they’re fully doing this, but the term is fine.
Do you have a better proposed phrase?
But stating it plainly like this would make the contradiction too obvious.
Though tbf corporate-speak and AI-slop are both insufferable in similar ways...
Releasing a new fable is an example of straight up vertical progress, releasing a more efficient preexisting opus that is more affordable is an example of horizontal progress, more efficient models rather than higher power models.
The blog post about slowing down is still just some weird self interested post, they want to govern themselves and impose distillation restrictions/gpu restrictions and used some weird blog post about slowing down and fear mongering as usual to justify it, its strange, but slowing down and stopping are not the same thing at all.
doesn't sound like a razor at all
that, they fully intend to 'pace'. hiring accenture is a good sign they need some justification theatre and a fall guy for this decision.
Pacing is very explicitly about RSI and similar training methods that will accelerate progress beyond our ability to comprehend it.
What the big players are trying with the current calls to slow things down, is the standard capitalism practise of trying to engineer regulatory capture. TBH I'm surprised those calls are coming so soon - they must be really worried about running out of what little moat that they have.
Simply make them something that derives a text response from its training data.
The only good news is that these models are genuinely helpful and we have competition at least between 2 companies.
Prices per 1M tokens Claude Opus 5.5 Claude Opus 5
Cache reads $0.20 $0.50
Input tokens $4 $5
Output tokens $20 $25
Cache writes $5 $6.25
If you are forced to reduce price despite raising capabilities, that certainly tells something about the market, and potentially about Anthropic future profitability too, since this model is their biggest topline contributor
It does work out to be a similar cost per task though
https://artificialanalysis.ai/models/claude-opus-5-5#intelli...
It is most of the pareto frontier.
https://artificialanalysis.ai/models/claude-opus-5-5?models=...
> Cache hits and refreshes on Claude Opus 5.5 are priced at 0.05x the base input price.
If they do the same for Haiku and Sonnet 5.5 then we should also see 5c/mtok and 10c/mtok cache read for those models, respectively. Still too high for Haiku IMO, Luna is 2c/mtok.
If 5.5 is any better, I might try to do agentic-assisted development instead of just telling fable to delegate
For long running tasks it is. That's what made Deepseek so cheap.
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've don't think Astra is a better model, but it's the first OpenAI one that seemed good enough for me. Definitely keen to try Opus 5.5 and see if this claim is real.
> 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.
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.
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.
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.mdIsn't this basically the model admitting it was trained on this? Otherwise why would it think a pelican svg is a usual request?
But its safe to say that pelicans on bicycles are disproportionally huge part of their training data
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 could see them accomplishing it and seeing gains like this in roughly the correct timeframe, and when I heard about that development I assumed the frontiers would probably jump on it.
How it works: https://miraflow.ai/blog/deepseek-v4-1-flash-causal-encoder-...
tired: AI startup attempting to publish a webpage
wired: a nonprofit founded in 1996
Ah, they're spreading their limits to all their models it seems. Definitely not a good thing long term in my opinion.
https://mimo.xiaomi.com/mimo-v2-6#co-scientist-for-materials...
ChatGPT 6 Pro answered it without issue.
Giving moral lecture is different than reality i guess.
The real answer is local instantiations where you don’t have to worry about poorly tuned guardrails screwing you over while you try to work.
Until eventually the Chinese models get good enough/the strategic balance shifts and they start locking everything behind closed weights the same way the US companies are doing.
Whilst I'm sure the top-end OpenAI/Anthropic models might be better, I've found their guardrails so twitchy (especially Anthropic) that I wouldn't try to use them for even vaguely security related work.
The safeguards really don't work well for a lot of long-running tasks on old code bases. A lot of my workloads last days to weeks and the single biggest risk to the workflow is random safeguards.
That kind of bullshit was the old Opus filters too.
If it's more like Fable now, then it would require a full 8K resolution scan of your butthole just to acknowledge that biology is a thing that exists without committing suicide-by-filter.
It's just a standard hero image + text for me, with no scrolling effects.
edit: @iAMkenough figured it out, it was because I have prefers-reduced-motion enabled.
I agree that it's sort of stupid, not a fan.
For a marketing page, it’s not the worst UX I’ve seen, but still slightly annoying.
Everyone that doesn't gets served some animated bullshit.
Yep, you're right. I tried on my phone and got the scroll through image.
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.
God I hope so
> Input and output tokens are $4 and $20 per million, 20% less than Opus 5. Cache reads (which make up the majority of agentic and coding work costs) are $0.20 per million tokens, 60% less than Opus 5. Opus 5.5 also generates output more than 30% faster than Opus 5.
Better than Fable, cheaper than even the last Opus. I use Opus as my main driver so this is very exciting!