[nichch]

My opinion is that you should wait for 6-12 months before making a purchase either way.

Open weight models are getting good. With GLM 5.2 now chasing Opus, I'm very excited to see a smaller model's distillation.

Plus, the OLED MacBook Pro should be released by then.

[speedgoose]

The OLED touchscreen MacBook is rumoured to be called MacBook Ultra now, and it has been delayed quite a few times. I will probably cost the same than a decent bike.

[cassianoleal]

> a decent bike

I bought a decent bike a few months ago for a few hundred bucks. I used it for commuting and for when I went to the park.

Of course, it depends on what kind of bike you meant and what you consider decent. Hopefully that illustrates the quality of that comparison.

[speedgoose]

My commuting bike is okay and in this price range too.

The MacBook Neo is also a good enough laptop.

In my opinion, a decent bike is something that wouldn’t limit you in races. No need to spend enormous amounts of money for marginal gains, but something that would do the job well. That’s an order of magnitude more expensive.

[gizajob]

MacBook Ultra Expensive (when equipped with 256 or 512 Gb of ram)

[Frannky]

This is my opinion too. Even if you buy hardware like a cluster of 8xGB10s or 4 A100s, they'll still be slow and a little dumber than what you're used to. We need to wait a little for better hardware. Lots of companies are pushing the frontier, so hopefully it'll come very soon.

Competition and innovation will hopefully make the bubble pop, and we'll get reasonably priced local hardware to run very intelligent models. Something like Talaas with GLM 5.2 would be pretty cool. Or Apple printing the latest model onto hardware—it would give a new reason to buy a new Mac every year (a new ai model with every new version).

[gizajob]

The hardware is here today for people prepared to tolerate mild amounts of latency. It’s easy to forget that computing tasks used to often take major amounts of time - rendering an audio file, rendering a video, transcoding – all kinds of tasks took minutes or even hours of the computer spinning its fans on maximum just to deliver the result. AI and agentic AI and diffusion is the next round of that - trading a small bit of your waiting time for phenomenal power. The datacentre builders trying to get you hooked on instant responses on the LLM platforms have made you think that a “good” AI responds instantly and completely interactively - they can still be brilliant with a bit of delay. And having a competent agent doing things on my local machine, it doesn’t really matter if it takes ten minutes or an hour or six hours to complete a task while I’m out doing other things.

[Frannky]

Hmm, I have access to A100s and a GB10, but if I use the models hosted there to code, I waste a lot of time waiting for answers and correcting errors. The amount of work I get done thanks to the quality and speed of frontier hosted models let me be insanely productive and have a lot of free time. I could use the slow local setup, but at what price?

[gizajob]

Well if all that was taken away from you and you had to go to the bank to ask for the money to rebuild so you could become as productive as you are now, what would that cost and would the bank loan you the money?

[FireBeyond]

The racks we're deploying are effectively GB300 NVL72s: 72 Blackwell Ultra GPUs 36 Grace CPUs, 20.7TB of unified HBM3e.

Works out to about 1.1exaflops of fp4. Networking is 800gbps.

120kW per rack.

[gizajob]

That’s a majorly impressive computer. What’s the price of that per rack? Deploying for what?

[FireBeyond]

$3-4M per rack. A variety of workloads...