Comment by zmmmmm
12 hours ago
It's very clear to me that however much you like Claude and Anthropic models, every professional user shoudl be actively cultivating a set of alternatives and fallbacks to use and seeking to ensure the overall ecosystem is as open, standardised and portable as possible.
Anthropic is highly opinionated, dogmatic and idealistic. They have made a pragmatic decision already to cut loose a whole swathe of users so they can pursue areas higher up the value chain. that was essentially the original decision they made when they went after software engineering instead of general users. The fact they are repeating this over and over by continuing to carve out sets of users and usages they don't want reinforces this as a persistent core principle rather than a single pragmatic business decision.
What this means is that at a higher level, their core principle is to sacrifice users they don't "need" rather than provide a broad, accessible service. Which means in turn, you have to accept that when your usage conflicts with their interests, you are at very high risk they will cut you out. If you already depend on Anthropic in any critical path of your daily life, this will be a significant issue.
Why, though? I have half a terabyte of VRAM in cards in a datacenter and it’s absolutely not clear that anything I’ve learned using these to program or inside an app has taught me anything significant.
I talked to my friend about all the things I do to ensure my personal assistant behaves reasonably. The prompt engineering, the fake site evals, everything. And then I have Opus 5.5 do it and it doesn’t need anything. It’s simply fully aligned to performance by default.
And what did I learn anyway. Going from one model to another changes what works. And you can simply learn everything from the Chinese model in days. The whole “building skill” thing is bogus.
I have this library of techniques, a scant few of which I’ve made available on my blog, and what is reality instead: the next model blows the need for the techniques into the dust. Back on level playing field.
It’s a false god, this cultivation. Waste of time. Use the best model you can. Once you hit the guardrails move out to the other models. Even Opus 4.8 is fine. If you legitimately want to dodge the guardrails use the -cyber models.
Then move on. The library is dust.
There is a tribe in Ecuador, the Huaorani. They were only brought into contact with the world 70 years ago. Because they live at the equator, they never needed to think ahead to store food over the winter. They could see that the oil companies were destroying their land by polluting it with spoil from operations, cutting down swaths of the forest, etc, and they became activists pushing back against this; but a good hunter who can hand out food to others is very highly regarded in their culture, so they would queue for handouts from the oil companies and became dependent on them, doing low-wage work. When I read about this years ago, I thought that people from modern cultures would not be so naive, but I see that I was wrong.
I haven't used an Anthropic model, or GPT heaviliy in a year. And I have access to both, I dont support either of those companies. I think they're both led by genuinely evil people.
Agreed. Same. Except for work where I can use GLM, so I Opus 4.8
Care to elaborate why "they are led by evil people", and what AI companies are "not led by evil people"?
8 replies →
Can you share your reasoning about Antrophic being genuinely evil?
This was all fake then?
https://www.anthropic.com/news/statement-department-of-war
5 replies →
actively cultivating a set of alternatives
Absolutely. I have been [cyber]'d so many times even Claude jokes about it now. Claude is great but it's operators are making it unreliable for me. I have moved one of my projects elsewhere and will move the remainder tomorrow as a stop gap until I get the right hardware set up to run abliterated local models for some percentage of my needs. Their message has been received loud and clear.
Issue with Opus is that you can’t do regular pr reviews where you say please try find security issues at best there is silent refusal and worst you get downgrade.
best part is, if you actually know what you're doing, you cna absolutely get it to find bugs/vulns/etc. so it just really about preventing long horizon agentic tasks or people who don't know what they're doing or those who are doing legit non-offensive security sfuff
What's ridiculous is this is all futile. Anthropic will go through all of this effort of attempting to block these things and it will be for nothing in the end.
For those who do not play with Local AI much. Qwen4 was announce to be released the first week of Nov. The preview for qwen4 is currently one of the best local models you can use, and is roughly opus 4.6 quality on local hardware that costs 3.5k-4k
Many people are expecting it to sit somewhere above Opus 4.8 to opus 5 (not above, but the unquanted version of their largest model is expected to perform around here)
Anyone who cares to keep their current capability should definitely be looking at localAI and using it for at least their more routine tasks , even if it is qwen4 27B quant 4 on their gaming rig.
Wants to know what year the $3.5-4k estimate is for. My m4 max was $4k but sure can’t buy anything like that for $4k now.
M5 pro Mac mini with 64gb is $3k
If the weights aren't released yet it isn't a "local model".
That said, I hope there is a Qwen4 max. Because Qwen3.8-Max is the only thing that comes close to Kimi K3. We need competition in the open-weights space.
The preview for qwen4 == qwen3.8 flash next. And that is released currently.
I believe they have confirmed there will be Qwen4 Max, Plush, Flash, and 27B as the 4 open weights they plan to release. Starting next week, but they didnt specify if they plan to release all 4 at once, or if they plan to just release one of them, and trickle the others out over time. (They likely will do the latter to stay in the news longer)
1 reply →
They are likely talking about Qwen3.8-flash-next which is the new architecture for Qwen4
An NVFP4 runs at nearly 80 tok/s on the DGX Spark
They keep doing anti-competitive things over and over again, and the end users seems to refuse to see it. They do whatever they can to get vendor-lock in.
We see it, but they dont have a competitor. OpenAI cant compete and they are the closest. I have both for work, and Opus 5.5 is in a league of it's own. I use opus for everything until it bitches, and I use openAI for whatever it bitches about just to get past it.
At this point, I would like to consider other options, but if I want to get work done, opus 5.5. Hell even sonnet 5.5 is better than anything OpenAI has to offer when it comes to coding.
which kind of works exactly?
there is a huge difference between open models/other models/opus5.5 performance on, say, enterprise CRUD vs one shotting games vs embedded development vs pure algorithmic complex stuff vs cybersecurity stuff.
In my case "real work" is enterprise programming, while side projects are gaming stuff, so I'm better served by chinese open models on real work and opus for non-real work.
In my experience GLM5.3-4 are perfectly en par with opus 5.5 on pure enterprise CRUDs (basically 95% of enterprise programming) while GLM seriously lacks on game development.
the other aspect of real work is cybersecurity to me, and Opus5.5 and other models are very limited by their own safety, I have digital twins of our infra and I want LLMs to actually write full exploits on it, opus and openai just refuse to do it, GLM more than once got it there and showed me how it chained everything to actually break in the system and I could go around and fix stuff at all levels.
I'm also dabbing in training LORAs for smaller open models to do data entry and little more (RAG and the likes of it), because that costs a lot of tokens when you pay for them and it makes sense for a company to flat out buy a server with a few H100/200 to do it when you look at the TCO, I've already hit safety limitations when using Opus5.5 to help me through this.
Anthropic has plenty of competitors. We don't need the best model for most tasks these days. Open weights are making huge inroads for a reason.
10 replies →
Oh, I see it. But there is nothing that competes with Opus 5.5 for 90+% of the work I do, so I use Opus 5.5 for that 90%.
Mr. T pities the fool who has not tried Kimi K3.
4 replies →
What kind of work you do? I'm doing Linux kernel work in my free time, arguably one of the most complex coding task you can do, and the open source models are sufficient
There is nothing comparable. I will take Opus5.5 (or even 5.0) over Astra for almost any workload. OpenAI's models are just too misaligned to work well outside their benchmarks, or a strict environment with very clearly defined goals and constraints.
And I've spent around $100-$120k in api calls this year (total, both providers). Terra is awesome (price-performance) on noncreative things, but I don't allow it to write anything besides one-off scripts. Astra is decent for adversarial review, but only when you watch closely for her to not derail project into directions that are away from goal but safe to build, and Sol I honestly don't know where I'd use.
Her? Are we really giving them pronouns now?
3 replies →
Fortunately it is not a one horse race. GPT 6.1 Sol is an excellent model, sure it has some weaknesses (e.g. frontend design), but it also has strengths too (e.g. computer use / control; which is great for automated E2E QA).
On software engineering I find it's generally close enough to Opus 5.5 where it's more situational and even personal preference / skills / prompting style on which is better.
Most importantly, while neither company are saints, I don't curse at OpenAI models for classifiers anywhere as much as Claude models.
> but it also has strengths too (e.g. computer use / control; which is great for automated E2E QA).
Using 6.1 Terra for E2E workflow testing feels like cheating. I thought it would have all kinds of problems with the action space on certain steps, but it runs like a deterministic unit test.
I am convinced that OAI has the superior models for most practical scenarios. I've tried Claude recently and it makes me wonder if some of yall aren't actually massive trolls. It's genuinely not in the same room of performance if you place one foot outside junior programming or shiny blog posts about rewriting factorio to run on a ps2.
Claude has really really good vibes. I'm not sure why, but it feels more pleasant to interact with than other models.
The general sentiment is to de-risk from US Big Ai, because they are largely all doing these same things
They are doing similar things, yes; but they are not the same especially when it comes to `cyber` classifiers, or the extent to which these models will assist you with ML and AI research.
I find that logic similar to thinking both political parties are the same.
1 reply →
Things are about to get even shittier in the near future, when shareholders get involved.
Their entire “PBC” governance structure was designed from the beginning so that they could entirely avoid accountability to shareholders. Their board answers to no one.
I suspect when the company eventually falls prey to the intractable economic forces they’re up against (Google, OAI, Deepseek, commercial real estate, power) and the company goes bankrupt and gets stripped for parts because all inputs are commodities and capital becomes the only limiting factor, we’ll see regulation that prevents this PBC scam from ever being pulled again on public markets.
It’s a good thing that companies have a fiduciary duty to their shareholders. It’s such a lesswrong/autistic trope to invent these kinds of complicated tricks to work around realities they don’t like, and when pension funds and everyday Americans start bagholding their junk debt and are forced to bail them out, they’re going to face unimaginable blowback.
The real problem is everyday Americans invest in big managed funds where they can't just say "I don't want AI stocks please leave them out my portfolio". Or index funds where even the managers don't get that choice. We need a hybrid model where you as a retail investor leave the day to day decisions to an expert but you can always override them if you want to.
Fiduciary duty forces companies to maximize profit and that's not a good thing. Every dollar paid out to shareholders is both a dollar not invested in growing the economy through more production and a transfer from the working class to capital. It also forces lower product quality, layoffs and anti competitive actions.
We need more companies that choose to not go down that path. They should just put workers and customers first instead of their weird "ethical" principles and cult like beliefs.
Fortunately, once shareholders get involved we would be entering the swan song phase, so wouldn't have to suffer for long.
Idk I expect being beholden to shareholders and the market will impose some level of rationality here
You mean: stop caring if a few individuals have issues with the product or get locked out, focus on the masses!
Actually cutting off potential users would probably be counter to short term profit maximization that shareholders care about.
> Actually cutting off potential users would probably be counter to short term profit maximization that shareholders care about.
Shareholders know where the money is but it's not where you think it is. People should have learned that already, after watching what happened to the big web platforms.
idk i think theyre less idealistic and more monopolistic.
if they think their model is the best at making things safe, then their model should be helping train at any chance, to embed the same safety into new models
They want to do one thing and do it well.
Well, arguably so does OpenAI, but their one thing is "assimilate all life forms into the Borg."
It’s not professionals that need to something- it’s absolutely critical we have some kind of credibly neutral body providing the actual models. What’s not clear at all is how to do that since it’s such an expensive activity.
For now we have a great situation with the open weights, but there is absolutely no guarantee that continues, and more the opposite- they may stop.
Anthropic is acting like any regular selfish corporation despite their PBC status. They are becoming a stain on humanity. Power will corrupt anyone, it seems. We shouldn’t let Anthropic have any more of it. Distributed power is good; concentrated power is very bad.
Anthropic tells themselves that only they can steer AI towards a positive future for humanity. But that’s nowhere near close to being true. Humans are quite genetically homogenous and good humans exist everywhere. Groups that will keep AI beneficial have popped up (and will keep popping up) everywhere, spontaneously.
The danger is actually concentration of AI power due to its corrupting influence, and that is where Anthropic needs to be kept in check. Keep AI democratic through decentralization of power. Oppose Anthropic.
What’s the best local analog to Opus 5.5? It’s such a great daily driver.
There is nothing open-weight that even comes close IMO. The only half-decent model that 99% of people can actually dream of running locally is Qwen 3.8 27B.
Depends what you mean by running locally, but it's not in the realm of dreaming to think we're going to be able to run open-weight models of Opus 5.5 quality soon, likely in the next 3-6 months. You may not be able to run it on your laptop but you will be able to run them in a federated way or on cloud-rental compute cheaply and easily.
I think this is an unfortunate reality that many miss. For simple and procedural tasks, yes, there are awesome alternatives. DeepSeek 4.1 Flash 1017 is my favourite by far. But for the headlining complex applications, and for consistently reliable reviewing, the gap is genuinely so remarkably far that it is hard to imagine having any alternative in the near future. The closest is the (very expensive) Kimi K3.1 Pro, which is, in my experience, roughly where Anthropic and OpenAI were near the start of the year. DeepSeek is a year behind in this domain. All open models have still yet to cross that monumental improvement that happened around Fable / Sol mid-year.
Because rigour is typically tied to math performance, my own experience has closely matched the FrontierMath Tier 4 benchmark. That should give you an idea of the difference.
3 replies →
It's odd, a year ago the models then were a great daily driver, and a year before that too.
Going back to the model that was great for our daily work a year ago now seems like a step backwards. Clearly it can't be good enough?
But our work hasn't changed. What's happened is our expectations have changed with each model release.
I think the key part is not to depend on their harness where it operates in proprietary ways. At bare minimum, if you can plugin an OpenAI model or even X or Google model that operates close to the same level, you will have a fallback, even if it isn't an open one itself.
Yes, open models are needed too - the oligopoly is not much less dangerous than the monopoly for some scenarios. But at least if your tool set can switch to those it can probably switch to an open model if it really comes to that.
Unfortunately, their harness is sooooo good. I haven't found one equivalent yet. I do play around with cline.bot's harness, and it is probably the closest alternative I have found.
But their harness is so good, and their model is so good. Using them together is just unbeatable at the moment, even with all the restrictions and annoyances they have in place.
Im excited for qwen4 release next week, Im really looking forward to putting qwen4 flash + cline/bot through the paces. I dont expect it to be nearly as good as Opus5.5+Claude but I'm hoping im hopeful it will make an OK-Enough alternative if they get even more dragocian.
3 replies →
There isnt one.
The best option we have current is likely Qwen 3.8 Flash Next. Which is about equivalent to Opus 4.6
however Qwen4 was announced to be released next week. Which people think will let LocalAI jump to just above Opus4.8
Also of note, there isnt really a harness as good as claude yet either. The harness is also a very important piece to the puzzel, and those also fall behind frontier capability too.
As of today, DeepSeek V4.1 Flash 1017 or Kimi K3.
If you are bound to consumer-obtainable hardware, Qwen3.8-Flash-Next. If you are bound to consumer-accessible hardware, Qwen3.8-27b today and Qwen4-27b when it releases next week (Qwen models consistently punch far above their parameter size).
Flash is runnable in various gpu + cpu offload configurations. Not saying that 27b is bad (far from it, especially if they get n-grams in it with... hopefully today's release), saying that flash is runnable at decent speeds on way less than you'd imagine.
As for opus... I'm the weirdo that refuses to get an ant sub.
2 replies →
I think Kimi K3.1 steals the crown from K3, no?
3 replies →
Same here with GLM 5.3 as sort of a midpoint between them.
GLM has the ~same number of weights as DeepSeek 4.1 but it handles difficult tasks better than DeepSeek (and worse than Kimi). Its price is about halfway between DeepSeek and K3. Most of the popular models are pretty much you-get-what-you-pay-for.
Local is out of reach for most folks, as hardware prices have gone through the roof.
> They have made a pragmatic decision already to cut loose a whole swathe of users so they can pursue areas higher up the value chain.
This referring to cyber? Bio?
To the dismay of frontier labs, swapping models is actually very basic. What takes time is only acclimating to the capability changes since they won't all change linearly.
I don't care about my skills because employers won't request me to do anything that violates the terms of service of $CURRENT_LLM. At the same time, it's a reminder not to outsource thinking to someone's computer.
Now do OpenAI.
“you have to accept that when your usage conflicts with their interests, you are at very high risk they will cut you out.”
I thought…
we learned this Facebook.
We learned this with Google.
We learned this with Apple and the App Store.
We learned this with Twitter.
We learned this with Heroku.
Unfortunately humans as a society dont learn from history.
They learn from personal lived experiences that have occurred only recently within their lifetimes. (Ie. Mass unemployment, death, famine and war)
I thought we have learnt from Microsoft, and my father thought we learnt from IBM, my grandfather thought we learnt from AT&T, my grandgrandfather thought we learnt from Standard Oil..
It's not just the anti-competitive behaviour, it's also the anti-privacy behaviours that are not muched talked about. They embedded a spyware and got caught too:
https://thereallo.dev/blog/claude-code-prompt-steganography
But, of course, Dario is the darling of the community and he can do no wrong.