Vultr is pretty cool, but I was paying $10/mo for a 2 v-cores/2gb/55gb. I got a 'root server' with netcup and I'm now paying $11/mo for 4 cores/8gb/256gb nvm-e. Unfortunately the placement isn't what I hoped as it's in Virginia. I would've liked Singapore but the cost would be twice as much.
No, just a regular Pro subscription. Apparently it's not just me, Github seems to have removed these models from the "Student" subscription [0] but it seems as it was also removed from regular "Pro" subscriptions as there are many reports on their discussions. [1]
Yeah, I got the email that they removed them from the student plan:
"As part of this transition, however, some premium models, including GPT-5.4, and Claude Opus and Sonnet models, will no longer be available for self-selection under the GitHub Copilot Student Plan."
They specifically said this was primarily for student plans. I'm surprised they did this for the normal pro plans too; it's likely a mistake since the plans page[1] still says that the models will be available.
However, TBH, I've never liked Microsoft's flavor of these; they always seem lobotomized compared to using the models directly in Claude Code / Codex. I rarely use AI in VS Code because it's just bad.
> the next generation of Ai companies will be easily valued at 10T
I'm not sure where this conclusion is coming from. We're very likely already in an AI bubble so I'm thinking that open/free models will eventually dilute the huge ridiculous valuations these companies have. Also the natural increase in consumer hardware power will eventually allow many people to just use local models instead both for privacy and cost reasons.
And seeing as most models are essentially only improved versions of the previous ones with larger context and more training data, unless some new "Attention Is All You Need" paper comes out that will give us a big step into AGI territory, I'm really not seeing a new company reach $10T valuation by just releasing marginally better models every couple of months imho.
I am know you consider yourself a pragmatist but zoom out a little and think about it again.....these idiotic humans built a couple of 1T companies with a stupid genAi algorithm in less than 50 year. in 2100, very high chance they will do 10T
I'm in the process of building v2.0 of my app using opus 4.6 and largely agree with this.
It's pretty awesome but still does a lot of basic idiotic stuff. I was implementing a feature that required a global keyboard shortcut and asked opus to define it, taking into account not to clash with common shortcuts. He built a field where only one modifier key was required. After mentioning that this was not safe since users could just define CTRL+C for the shortcut and we need more safeguards and require at least two modifier keys I got the usual "you're absolutely right" and proceeded to require two modifier keys. But then it also created a huge list of common shortcuts into a blacklist like copy, cut, paste, print, select all, etc.. basically a bunch of single modifier key shortcuts. Once I mentioned that since we're already forcing two modifier keys that's useless it said I'm right again and fixed it.
The counter point of this idiocy is that it's very good overall at a lot of what is (in my mind) much more complicated stuff. It's a .NET app and stuff like creating models, viewmodels, usercontrols, setting up the entire hosting DI with pretty much all best practices for .net it does it pretty awesomely.
tl;dr is that training wheels are still mandatory imho
> I keep switching among these subscriptions every month to not miss out on any of the offerings for too long; ChatGPT Plus <-> Gemini Pro <-> Claude.
I wonder why many people seem to be doing this instead of just going for a copilot subscription that has access to all those models? Anybody care to share pros and cons?
OpenAI and Anthropic give you a lot of usage/$ through their plans. For the Anthropic Max plans, this can be like a ~90% discount. Copilot does not benefit from this (their pricing model is also different though, it is request-based rather than token usage based, so it is hard to compare).
That's not to mention that the models generally work better in their own harnesses, which is perhaps unsurprising because the models have been trained with the specific harness in mind (and vice versa). That said, I think some 3rd-party harnesses do a lot of work to make different models work well in their harness.
Still an awesome service and platform.. but no longer worth it price wise as it once was. Same with Vultr..
I guess at some point all investors just pressure these companies into price matching AWS and other pay-for-every-single-thing-ever companies.
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