Comment by Sammi
6 hours ago
I'm a small software business owner in Europe. I have to assume my competition is willing to pay for any business advantage they can get. And so I also have to pay for the SOTA model, whatever it is.
6 hours ago
I'm a small software business owner in Europe. I have to assume my competition is willing to pay for any business advantage they can get. And so I also have to pay for the SOTA model, whatever it is.
No you don't; it's often overkill to use the SOTA models. People want SOTA because it's shiny, but there are a lot of tasks where it's cheaper and more efficient to use other models.
The good news (for you and most everyone other than the current leading AI companies), the gap between the SOTA and the near-frontiers is getting smaller every week or two. The leading Chinese models are only a few months behind now (GLM 5.2 tickles the tail of GPT 5.3 or 5.4 and Opus 4.6, according to benchmarks and the vibes among heavy users who've spent some time with it), where they were a couple of years behind a year ago.
4.6 was released at the beginning of February, so if the Chinese models only "tickle its tail," that means they're >5 months behind.
That comparison is also misleading because Opus 4.6 was probably not Anthropic's frontier model.
We got the first news about Mythos in March, so it is likely that it was already close to ready by the time Opus 4.6 was released.
So the actual gap is the time elapsed between March (or April for the official announcement) and whenever Chinese models can match Mythos.
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> The leading Chinese models are only a few months behind now
What range of numbers do you believe "a few" represents?
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This is nonsense.
The gap between Chinese models and American frontier models is estimated at 10 months by Anthropic themselves, and it's growing.
China has no flywheel for long-form agentic traces like Claude Code and its telemetry over its userbase (no one uses the Chinese harnesses yet). Most Chinese models are forced to price themselves significantly below cost to compete with the huge demand for bootleg claude tokens, because they're that much worse.
Here in Australia the sudden withdrawal of Fable made all of us think hard about models and harnesses.
I've heard half a dozen people talk about how a less advanced model coupled with a better harness outperforms a smarter model in the last few weeks.
If the USA wanted to shoot its AI industry in the foot it achieved its goal.
> is estimated at 10 months by Anthropic themselves, and it's growing.
How is this different than any business with something to lose saying a competitor isn't as good? Not saying it's false, but it would seem to me that it's more important how customers feel about the issue.
If Anthropic themselves say competition is 10 months behind, it's probably 5 or less.
And you seem to think "no one uses" DeepSeek's v4, z.AI's GLM 5.2 or Xiaomi's MiMo 2.5 from their official APIs when they probably dwarf Anthropic's usage and are widening the gap due to conquering a chunk of Western market too.
I know it's hard for some to comprehend there's an entire Eastern hemisphere in the globe with billions of people, so it's worth reminding. And some seem to think the world is basically silicon valley even.
Another day, more cope on this subject from many posters on here...
I don't know if you write software for your own products or if you code for your customers. Anyway, are you going to compete on the speed of your code writing AI or on deploying the features your customers need? One useful feature is better than a hundred ones nobody really care about. And a good relationship with customers is better than any feature.
Example. Yesterday I listened the technical lead of a customer of mine digging himself into a hole by not understanding what it would mean exposing AWS EFS to their on premise server over NFS. It was just too many unknown unknowns for him and he had no time to ask the AI (and even if he did I'm not sure that he could understand.) His boss, which actually used NFS, had to stop him. I didn't speak a word.
So, he could have coded the migration of a server from AWS to on premise, asked Claude to write also all the configuration scripts and policies but then what?
This is a great recipe for going out of business.
If the competitive risk is real, then are choosing between supplier risk (AI model access) and competitive risk.
When there isn't a zero-risk option, the question becomes which risk is smaller.
> If the competitive risk is real
Yes.
If.
Man I hope this tech FOMO eventually stops.
Companies generally fail because either their product doesn't meet a market need, or the market doesn't exist in the first place (possible because of bad timing), and not because they simply outran their competitors.
These aren't things fixed by using a frontier model to vibe code faster in lieu of one 5 months behind.
You can compete by being smart and using less-than-sota models and build a more solid business around them
Any competitive business will accept this risk if it gives them any type of edge no matter the duration of that edge. This is no different that using an exotic raw material.
Every big business in the world biases towards risk reduction and cost reduction over getting an edge.
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Eh, this isn’t really how businesses operate. How many businesses refuse to give devs large-spec machines? That’s very clear positive ROI.
I think it’s excessively charitable to assume businesses are uber-competent ROI-chasers. The expense people are eventually going to win on AI too, this blip of unrestricted AI budgets will be gone soon.
And thus, capitalism continues to roll on. Businesses are suppose to go out of business, its a feature.
they’re not supposed to, they’re just able to
Nearly spit out my coffee, thanks for the chuckle.
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What concrete business advantage are you getting from LLMs?
Speed.
This x 10 . I don’t understand how people are saying you can’t use LLMs to get crazy productivity gains. If you can’t write quality code with LLMs at ludicrous speed, you’re holding it wrong. You will have occasional bad days and regressions. But overall you’re still going to be able to 4x your progress.
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>> What concrete business advantage are you getting from LLMs?
> Speed.
Speed of what?
Speed of understanding what needs to be done? I highly doubt it.
Speed of LoC checked into git? Sure, I'll give you that.
But one can use any number of tools to generate hundreds of thousands of lines of code. See any build tools which support specifications such as RAML, OpenAPI, CORBA, etc.
So I ask again; speed of what?
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From my brief window of Fable usage, speed wasn't its strong point at all.
For actually building software, I'm starting to suspect a human with a dumber (but faster) model is going to get the job done quicker than Fable (and possibly even cheaper). Bug-finding and vulnerability detection is a different story.
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Drawing debt
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If you can't figure out what model to use your business is already dead.
This thinking that every task must be stuffed into the most 'advanced' (expensive) model out there is idiotic, and it's not only you unfortunately.
At $JOB I have warned higher ups we should try to keep our expenditure under control, educate people that document slinging doesn't require Fable every time and demo the capabilities of the cheaper models, and been snubbed for it. When Fable is available once again our bill is going to be eye watering, relative to what it should be.
This! I've found that for most coding, Sonnet is pretty good as it is. Yeah, you might need to finesse your prompt a bit more, and you'll probably be spending a bit more time on the computer, rather than a more hands-off approach, but at the end of the day, you'll save a lot more simply because you're using a good-enough model.
If you're the one-shotting type, obviously then Fable might be useful, but I think only marginally. You don't need to bring a MANPADS to a duel at high noon.
Sonnet is dogshit at coding unless you eval the exact niche to be fine and still watch it like a hawk.
do you think your current operation and niche is so optimized that not using Fable would put you out of business? Or is this a hope that using Fable will allow you to stay in business?
I am on track to commoditize my niche industry, and I hope I can do it before anyone else beats me to it. I'm working at panic speeds.
So, no moat right?
So the panic generators ("You will be left behind!") are winning. Creating a sense of urgency that makes you switch off the higher rational functions is a key element in every successful scam.
Unless you have concrete evidence via evals that SOTA is actually needed, you’re just buying into the hype.
Nonsense. Do you buy state of the art pens, pencils, printers, paper, computers, disks, etc.? No. You buy whatever is the best value for the case at hand. That’s often not the SOTA option.
Sure but that's orthogonal.
Yes you use the right tool for the job.
But if the job requires the best intelligence you can get with an LLM, then you use that.
Taking as an assumption that the quality of your product is a function of the quality of the inference you are using: if you use an inferior model because "what if it gets export controlled again" and your competitors don't, then your competitors are likely to win.
If you don't need frontier models for you job then this is all moot, but the thread started with
> You cannot build a business critical function on top of American SOTA frontier model
Which is silly. HN likes to roleplay bringing everythgin "business critical" in house because sometimes vendors mess up. Self host, don't use the cloud, run open models locally, built redundant supply chains in case of another covid, etc etc. Sometimes the risk is real, but most of the time the risk is rare and the cost of an interruption event is less than the cost of bringing everything in house or using lower quality vendors "just in case"