posted in Technology
OpenAI Hoarding Tens Of Thousands Of Apple Mac mini And Mac Studio Devices, As ASUS And MSI Burn Through Their Entire First Batch Of NVIDIA RTX Spark Chip And Beg For More.
wccftech.com/openai-hoarding-tens-of-thousands-of-apple-mac-mini-and-mac-studio-devices-as-asus-and-msi-burn-through-their-entire-first-batch-of-nvidia-rtx-spark-chip-and-beg-for-more/
Has the computers for local AI become that good?
Replying to @xSikes@feddit.online
No, no, they have not.
I did the math the other day, and the cost of the mac versus the token rate that you get off of it for a decent model would take you over 70 years of 100% 24/7/365 usage to pay for itself versus just using hosted inference.
They are wildly poor options for local AI models, at least on a cost basis. If you don’t care about spending $10,000 to run a halfway okay model at 100x the cost, then go for it.
Replying to @douglasg14b@lemmy.world
Well local models are getting better. Open weight models are a real thread to their business. OpenAI’s prices certainly wouldn’t stay that low if they were the only player. Their prices are not profitable at the moment anyway.
Replying to @berty@feddit.org
They really aren’t.
Have you used open weight models for serious jobs? Ones that you can actually run effectively on a Mac studio? (Not deepseek v4 pro, not Kimi K3, not GLM 5.3)
They work alright, at best, sometimes.
And the ones you can’t run effectively, locally, like Kimi K3 are considerably better at demanding tasks like software engineering. But even then they still suck at that job compared to frontier Anthropic and OpenAI models. I’ve been building with all of the above, and the open weight models just overall suck at serious high demand software workloads.