Measuring Claude 4.7's tokenizer costs

Post by al_borland » Fri, Apr 17, 2026, 9:51 PM UTC

smt88 wrote: post #289

al_borland wrote: post #274

Earlier quoted context omitted.

This seems like the experience I've had with every model I've tried over the last several years. It seems like an inherent limitation of the technology, despite the hyperbolic claims of those financially invested in all of this paying off.

Opus 4.6 pre-nerf was incredible, almost magical. It changed my understanding of how good models could be. But that's the only model that ever made me feel that way.

Post by slopinthebag » Fri, Apr 17, 2026, 10:04 PM UTC

_345 wrote: post #136

arcanemachiner wrote: post #98

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I want to give give you realistic expectations: Unless you spend well over $10K on hardware, you will be disappointed, and will spend a lot of time getting there. For sophisticated coding tasks, at least. (For simple agentic work, you can get workable results with a 3090 or two, or even a couple 3060 12GBs for half the price. But they're pretty dumb, and it's a tease. Hobby territory, lots of dicking around.) Do your…

We need more voices like this to cut through the bullshit. It's fine that people want to tinker with local models, but there has been this narrative for too long that you can just buy more ram and run some small to medium sized model and be productive that way. You just can't, a 35b will never perform at the level of the same gen 500b+ model. It just won't and you are basically working with GPT-4 (the very first one…

Post by skydhash » Fri, Apr 17, 2026, 10:09 PM UTC

Aperocky wrote: post #301

highfrequency wrote: post #194

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I believe that's why 90% of the focus in these firms is on coding. There is a natural difficulty ramp-up that doesn't end anytime soon: you could imagine LLMs creating a line of code, a function, a file, a library, a codebase. The problem gets harder and harder and is still economically relevant very high into the difficulty ladder. Unlike basic natural language queries which saturate difficulty early. This is also w…

> the dimensionality of LLM output that is economically relevant keeps growing linearly for coding Doubt. Yes. there was at one point it suddenly became useful to write code in a general sense. I have seen almost no improvement in department of architecting, operations and gaslighting. In fact gaslighting has gotten worse. Entire output based on wrong assumption that it hid, almost intentionally. And I had to create…

Post by skydhash » Fri, Apr 17, 2026, 10:14 PM UTC

conductr wrote: post #326

Bridged7756 wrote: post #169

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Its enshittificating real fast. They'll just keep releasing model after model, more expensive than the last, marginal gains, but touted as "the next thing". Evangelists will say that they're afraid, it's the future, in 6 months it's all over. Anthropic will keep astroturfing on Reddit. CEOs will make even more outlandish claims. You raised a good point, what's a good metric for LLM performance? There's surely all the…

This is most likely trajectory I fear. It reminds me a lot of Oracle, where they rebrand and reskin products just to change pricing/marketing without adding anything.

Post by captn3m0 » Fri, Apr 17, 2026, 10:17 PM UTC

Bridged7756 wrote: post #177

qq66 wrote: post #42

This is the backdoor way of raising prices... just inflate the token pricing. It's like ice cream companies shrinking the box instead of raising the price

No, you're forgetting the never ending world shattering models being released every couple of months. Each one with 2X token costs of course, for a vague performance gain and that will deprecate the previous ones.