They are also giving away $50 extra pay as you go credit to try Opus 4.6. I just claimed it from the web usage page[1]. Are they anticipating higher token usage for the model or just want to promote the usage?
Claude Opus 4.6
451–460 of 1001 posts
Re: Claude Opus 4.6
#452I think two things are getting conflated in this discussion. First: marginal inference cost vs total business profitability. It’s very plausible (and increasingly likely) that OpenAI/Anthropic are profitable on a per-token marginal basis, especially given how cheap equivalent open-weight inference has become. Third-party providers are effectively price-discovering the floor for inference. Second: model lifecycle econ…
> It’s very plausible (and increasingly likely) that OpenAI/Anthropic are profitable on a per-token marginal basis
There any many places that will not use models running on hardware provided by OpenAI / Anthropic. That is the case true of my (the Australian) government at all levels. They will only use models running in Australia.
Consequently AWS (and I presume others) will run models supplied by the AI companies for you in their data centres. They won't be doing that at a loss, so the price will cover marginal cost of the compute plus renting the model. I know from devs using and deploying the service demand outstrips supply. Ergo, I don't think there is much doubt that they are making money from inference.
Re: Claude Opus 4.6
#453Earlier quoted context omitted.
Can it draw a different bird on a bike?
Here's a kākāpō riding a bicycle instead: https://gist.github.com/simonw/19574e1c6c61fc2456ee413a24528... I don't think it quite captures their majesty: https://en.wikipedia.org/wiki/K%C4%81k%C4%81p%C5%8D
Now that I've looked it all up, I feel like that's much more accurate to a real kākāpō than the pelican is to a real pelican. It's almost as if it thinks a pelican is just a white flamingo with a different beak.
Re: Claude Opus 4.6
#454Earlier quoted context omitted.
> These feel like they involve something beyond "predict the next token really well, with a reasoning trace." I don't think there's anything you can't do by "predicting the next token really well". It's an extremely powerful and extremely general mechanism. Saying there must be "something beyond that" is a bit like saying physical atoms can't be enough to implement thought and there must be something beyond the physi…
> Besides, what is the human brain if not a machine that generates "tokens" that the body propagates through nerves to produce physical actions? Ah yes, the brain is as simple as predicting the next token, you just cracked what neuroscientists couldn't for years.
I mean.. i don't think that statement is far off. Much of what we do is entirely about predicting the world around us, no? Physics (where the ball will land) to emotional state of others based on our actions (theory of mind), we operate very heavily based on a predictive model of the world around us.
Couple that with all the automatic processes in our mind (filled in blanks that we didn't observe, yet will be convinced we did observe them), hormone states that drastically affect our thoughts and actions..
and the result? I'm not a big believer in our uniqueness or level of autonomy as so many think we have.
With that said i am in no way saying LLMs are even close to us, or are even remotely close to the right implementation to be close to us. The level of complexity in our "stack" alone dwarfs LLMs. I'm not even sure LLMs are up to a worms brain yet.
Re: Claude Opus 4.6
#455Earlier quoted context omitted.
What’s so simple about it?
I said relatively simple. It is mostly an API interface with Anthropic models, with tool calling on top of it, very simple input and output.
With extensibility via plugins, MCP (stdio and http), UI to prompt the user for choices and redirection, tools to manage and view context, and on and on.
It is not at all a small app, at least as far as UX surface area. There are, what, 40ish slash commands? Each one is an opportunity for bugs and feature gaps.
Re: Claude Opus 4.6
#456Earlier quoted context omitted.
There's a research paper from the University of Liverpool, published in 2006 where researchers asked people to draw bicycles from memory and how people overestimate their understanding of basic things. It was a very fun and short read. It's called "The science of cycology: Failures to understand how everyday objects work" by Rebecca Lawson. https://link.springer.com/content/pdf/10.3758/bf03195929.pdf
A place I worked at used it as part of an interview question (it wasn't some pass/fail thing to get it 100% correct, and was partly a jumping off point to a different question). This was in a city where nearly everyone uses bicycles as everyday transportation. It was surprising how many supposedly mechanical-focused people who rode a bike everyday, even rode a bike to the interview, would draw a bike that would not w…
This is why at my company in interviews we ask people to draw a CPU diagram. You'd be surprised how many supposedly-senior computer programmers would draw a processor that would not work.
Re: Claude Opus 4.6
#457Earlier quoted context omitted.
CC has >6000 open issues, despite their bot auto-culling them after 60 days of inactivity. It was ~5800 when I looked just a few days ago so they seem to be accelerating towards some kind of bug singularity.
Just anecdotally, each release seems to be buggier than the last. To me, their claim that they are vibe coding Claude code isn’t the flex they think it is. I find it harder and harder to trust anthropic for business related use and not just hobby tinkering. Between buggy releases, opaque and often seemingly glitches rate limits and usage limits, and the model quality inconsistency, it’s just not something I’d want to…
I think I would be much more frightened if it were working well.
Re: Claude Opus 4.6
#458I think two things are getting conflated in this discussion. First: marginal inference cost vs total business profitability. It’s very plausible (and increasingly likely) that OpenAI/Anthropic are profitable on a per-token marginal basis, especially given how cheap equivalent open-weight inference has become. Third-party providers are effectively price-discovering the floor for inference. Second: model lifecycle econ…
"how long does a frontier model need to stay competitive"
Remember "worse is better". The model doesn't have to be the best; it just has to be mostly good enough, and used by everyone -- i.e., where switching costs would be higher than any increase in quality. Enterprises would still be on Java if the operating costs of native containers weren't so much cheaper.
So it can make sense to be ok with losing money with each training generation initially, particularly when they are being driven by specific use-cases (like coding). To the extent they are specific, there will be more switching costs.
Re: Claude Opus 4.6
#459Earlier quoted context omitted.
Is there a way to disable it? Sometimes I value agent not having knowledge that it needs to cut corners
90-98% of the time I want the LLM to only have the knowledge I gave it in the prompt. I'm actually kind of scared that I'll wake up one day and the web interface for ChatGPT/Opus/Gemini will pull information from my prior chats.
All these of these providers support this feature. I don’t know about ChatGPT but the rest are opt-in. I imagine with Gemini it’ll be default on soon enough, since it’s consumer focused. Claude does constantly nag me to enable it though.
Re: Claude Opus 4.6
#4601M context window is a big bump very happy