• Claude Design uses Opus 4.7, which is more expensive than earlier models.
• It's just Day 2; it's not a finished product. It's ridiculous how quickly Anthropic iterates.
• If you've been using Claude for a while, Design already knows your style and preferences. You'd have to start from scratch using a different AI design tool. I don’t doubt that'll pay dividends in the long run.
We don't know that for sure—they've dropped prices before:
1. Claude 3 → Claude 3.5/3.7 generation (mid-2024 to early 2025): Haiku went from $0.25/$1.25 to $0.80/$4.00 per MTok — this was actually a price increase for Haiku, but Sonnet stayed flat at $3/$15 while delivering significantly better performance, effectively a price-per-capability reduction.
2. Claude 3/4 Opus → Claude Opus 4.5/4.6 (late 2025): This was the big one. Opus dropped from $15/$75 per MTok down to $5/$25 per MTok — a 67% reduction on input and output. This is the most significant explicit price cut Anthropic has made, delivering a far more capable model at one-third the price.
BTW, Github Copilot is pricing Opus 4.7 at 2.5x the cost of Opus 4.6 at promotional pricing (so maybe it'll be 4-5x). But Github's request based pricing is insane, completely divorced from their actual costs (you can achieve 1+M tokens for $0.10 if you give it a large request), so I'd assume they're losing a lot of money.
The cost of a thing, is relative to its source costs. They are subsidizing API pricing, if you consider all the costs to provide the service, including all model creation, training, etc costs.
But that doesn't mean they will be more expensive, longer term. The cost of compute will go down as time goes on. Each year it will get cheaper. Same for power requirements, computing density, cooling, and so on.
I remember trying to store and play mp3 files on older computers. I could typically hold a few on a disk, and if I wasn't doing anything else I could play one. Barely. Now you'll be hard pressed to play an mp3 and see the load results in top or what not.
The same will be true of AI in 20 years.
I want robust local LLMs as much as the next person—Gemma E2B, 3.2GB does my word completions as I type. It's gotten to the point where it knows what I'm going to type before I do!
But I don't see Anthropic going out of business anytime soon. As good as some of the open source LLMs are, we’re still a long way from being able to frontier models at home.
Everyone can do baremetal at home and run on it, or VMs, containers. Many don't.
However, you'll still want the best model and toolset. So there is some place for them to pivot to. Something for them to sell or licence.
It will be interesting to see where the all lands, a decade from now. Who will be left?
If you need LLMs at scale to serve many customers, then hosted solutions make sense for the availability aspect. But by this point models can be offered by any generic services provider, like AWS or Cloudflare. Pure AI companies that just offer hosted models and nothing else will go extinct if they don’t expand to offer more services.
LLMs a couple of years ago that'd be impossible to run on consumer hardware are now running on consumer hardware. I'm less concerned about compute power; it's more about memory.
It could be several years before new RAM capacity comes online. Even then, it won't be cheap.
I expect in the future, hosted frontier models will be a utility like electricity or cable tv. Part of a package most people will subscribe to.
AI is very emotional for a lot of people leading to bias takes in both directions. We like to think HN is more rational than average, but we’re all human.