61–70 of 89 posts
I see combined estimated revenue for Q1/2026 to be $15B to $20B, depending on source. I also see combined estimated spend Q1/2026 at $15 to $20B, depending on source. Someone or something is having an hallucination that would make an AI jealous
Is he headline strictly about subsidized subscriptions? Anthropic announced their first profitable quarter.
Article flagged by the HN moderators owning pre IPO shares on said companies discussed in this article: Anthropic, OpenAI and SpaceX
Hang on to your wallet, you ain't seen nothing yet. The true cost of AI won't be revealed until after a large portion of the customer base has become "hooked" on it.
“Hooked” is doing a lot of work there. I’m happily paying $200/mo for Claude code. The tokens I use would be >$10k at API rates. I’m building the best products of my life, and multiple of them in parallel. I’m doing better creative work, finally realizing a game idea I’ve had no time for, etc. If this level of usage goes to $500/mo… I’ll be out. It’s worth what I’m paying, but hey I went a decade without writing that…
Anthropic and openai has the most efficient tokens per unit of compute on the planet and honestly that's their current moat. They're able to serve tokens at half the cost of any opensource provider. Here's the costs to serve opus 4.7 in china on aws according to one of my connections that operates an enterprise account in the region: Input: $0.257 Output: $1.286 Cache read: $0.0257 Cache write: $0.322 And I have zero…
I see combined estimated revenue for Q1/2026 to be $15B to $20B, depending on source. I also see combined estimated spend Q1/2026 at $15 to $20B, depending on source. Someone or something is having an hallucination that would make an AI jealous
There are no revenue estimates in the article). Only as serious as possible estimates of cost per task.
banks used to lose a lot of money on those toasters, amazing they are still in business
If it is subsidised, fine – the incumbents absorb the losses, or lean on hyperscalers like Google or Microsoft who can cross-subsidise across other revenue streams. But if it isn’t, that’s the worse outcome for them: inference is just cheap, competition kicks in, prices crater, end users win.
Either way, local models win. If the incumbents are forced to turn a profit, pricing goes up and as local compute gets good enough to handle most use cases, people flock to it. And if inference is just cheap, that means the compute requirements are lower than we thought, and local hardware gets there even faster.
Bullish on local either way. We’ll find out once the Anthropic S-1 drops.
Anthropic and openai has the most efficient tokens per unit of compute on the planet and honestly that's their current moat. They're able to serve tokens at half the cost of any opensource provider. Here's the costs to serve opus 4.7 in china on aws according to one of my connections that operates an enterprise account in the region: Input: $0.257 Output: $1.286 Cache read: $0.0257 Cache write: $0.322 And I have zero…