201–210 of 374 posts
What people don't realize is that cache is *free*, well not free, but compared to the compute required to recompute it? Relatively free. If you remove the cached token cost from pricing the overall api usage drops from around $5000 to $800 (or $200 per week) on the $200 max subscription. Still 4x cheaper over API, but not costing money either - if I had to guess it's break even as the compute is most likely going idl…
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I'm surprised, isn't it forbidden to use the Max plan as part of a company? Just curious, as I thought it was forbidden by the ToS but I'm not sure if I have a good understanding of it
Most companies forbid it though, since you're not covered by any legal protection - for example, Anthropic can use your data or code to train new models and more.
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Everyone who's used Opus knows it's better than the others in a way that isn't captured by the benchmarks. I would describe it as taste. Lots of models get really close on benchmarks, but benchmarks only tell us how good they are at solving a defined problem. Opus is far better at solving ill-defined ones.
> Everyone who's used Opus knows it's better than the others in a way that isn't captured by the benchmarks. I would describe it as taste. Ah, the "trust me bro" advantage. Couldn't it just be brand identity and familiarity?
My dashboard goes from all green to 50/50 green/red for our agents whenever I switch from Claude to one of the cheaper agents... This is after investing a substantial amount of effort in "dumbing down" the prompts - e.g. adding a lot of extra wording to convince the dumber models to actually follow instructions - that is not necessary for Sonnet or Opus.
I buy the benchmarks. The problem is that a 10% difference in the benchmarks makes the difference between barely usable and something that can consistently deliver working code unilaterally and require few review interventions. Basically, the starting point for "usable" on these benchmarks is already very far up the scale for a lot of tasks.
I do strongly believe the moat is narrow - With 4.6 I switched from defaulting to Opus to defaulting to Sonnet for most tasks. I can fully see myself moving substantial workloads to a future iteration of Kimi, Qwen or Deepseek in 6-12 months once they actually start approaching Sonnet 4.5 level. But for my use at least, currently, they're at best competing with Athropics 3.x models in terms of real-world ability.
That said, even now, I think if we were stuck with current models for 12 months, we might well also be able to build our way around this and get to a point where Deepseek and Kimi would be cheaper than Sonnet.
Eventually we'll converge on good enough harnesses to get away with cheaper models for most uses, and the remaining appeal for the frontier models will be complex planning and actual hard work.
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I'd love to be a fly on the wall when this argument is tried in front of a bankruptcy court. It drives me nuts. Of course there's evidence that they're selling tokens at a loss. The only thing these companies sell are tokens. That's their entire output. OpenAI is trying to build an ad business but it must be quite small still relative to selling tokens because I've not yet seen a single ad on ChatGPT. It's not like t…
You're missing costs. - Amortized training costs. - SG&A. - Capex depreciation. All the above impact profitability over various time horizons and have to rolled into present and projected P&L and cash flow analysis.
In part due to base model reuse and all the tricks like distillation. But mainly, due to how much inference the big providers happen to sell.
So, not the massive economic loss you'd need to push models away from being profitable. Capex and R&D take the cake there.
Which is probably a lot more correct than other claims. However it's also true that anybody who has to use the API might pay that much, creating a real cost per token moat for Anthropics Claude code vs other models as long as they are so far ahead in terms of productivity.
A huge number of people are convinced that OpenAI and Anthropic are selling inference tokens at a loss despite the fact that there's no evidence this is true and a lot of evidence that it isn't. It's just become a meme uncritically regurgitated. This sloppy Forbes article has polluted the epistemic environment because now theres a source to point to as "evidence." So yes this post author's estimation isn't perfect bu…
I'd love to be a fly on the wall when this argument is tried in front of a bankruptcy court. It drives me nuts. Of course there's evidence that they're selling tokens at a loss. The only thing these companies sell are tokens. That's their entire output. OpenAI is trying to build an ad business but it must be quite small still relative to selling tokens because I've not yet seen a single ad on ChatGPT. It's not like t…
Why does Claude charge 10x for API, compared to subscriptions? They're not a monopoly, so one would expect margins to be thinner.
> Qwen 3.5 397B-A17B is a good comparison It is not. It's a terrible comparison. Qwen, deepseek and other Chinese models are known for their 10x or even better efficiency compared to Anthropic's. That's why the difference between open router prices and those official providers isn't that different. Plus who knows what open routed providers do in term quantization. They may be getting 100x better efficiency, thus the…
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Omg, I can't believe that's real I wanted to believe that you're essentially trolling, but no - that service exist. And not an upstart, there is coverage going back several years. Our societies are seriously fucked.