In fact, according to The Register, the GPU computing performance of the GB10 chip is roughly equivalent to an RTX 5070. However, the 5070 is limited to 12GB of video memory, which limits the size of AI models that can be run on such a system. With 128GB of unified memory, the DGX Spark can run far larger models, albeit at a slower speed than, say, an RTX 5090 (which typically ships with 24 GB of RAM). For example, to run the 120 billion-parameter larger version of OpenAI’s recent gpt-oss language model, you’d need about 80GB of memory, which is far more than you can get in a consumer GPU.
Or you could’ve just made GPUs, and then we’d all be gaming and calling each other shitheads in Valorant instead of - checks notes - literally stealing the water from poor communities.
If I had to come up with a steelman argument for small “AI focused” systems like this, I’d say that the more development in this space, makes the cost of entry cheaper, and actually eventually starves out the big tech garbage like OpenAI/Google/Microsoft.
If everyone who wants to use AI can locally process queries to a locally hosted open-source model with “good enough” results, that cuts out the big tech douchebags, or at least gives an option to not participate in their data collection panopticon ecosystem.
Unfortunately Nvidia is also big tech so starving out (sort of) competitors doesn’t help get rid of douchebags. It actually has the added risk of giving some of the douchebags a monopoly.
Buying one of those AMD Ryzen AI Max chips actually makes more sense now…
You can game with bricks. Or ball.
And throw away your notes. They are a completely disgraceful waste of paper.
Blocked for being a dick.
Well, he’s right. Most likely you’re “wasting” energy and water as well, just in a different manner.
The difference is your comment managed to say that without being a dick about it.
Ok, but can you use it as a PC?
