Somebody posted a photograph of a melted power socket on an RTX 4090 that had been fine for three years. They started generating video in mid August. By 20 September the machine shut down every time a render began. We cannot diagnose their card and neither can anyone else online, but the mechanism behind this failure class is documented, and it explains why a workload change can expose something a gaming load was hiding.
Micro Center has started asking RTX 5090 buyers for a government photo ID and a signed declaration naming where the card will be installed. It is not a law, it is not confirmed at every store, and the headlines are not saying either of those things. Here is what is actually documented, and what it does to the buy-or-rent decision we published last week.
Somebody on r/LocalLLaMA published their working on whether to buy or rent an eight GPU H200 server. We ran the same arithmetic for the card most people reading this would actually put in a desktop, and the answer has moved a long way in the last year. It is not the answer we expected, and we own the card.
A Mozilla analysis put the open to closed capability gap at about 4.4 months, and it went round the local AI world as good news. It is good news. It is also being read as something it does not say, because the open model doing the catching up is 2.78 trillion parameters and will never see the inside of your computer.
We took a stock Asus TUF gaming laptop with an RTX 3070 and 8 GB of video memory, and benched eight local models overnight across ten tasks. The result that surprised us: a 30 billion parameter model with two thirds of itself off the card beat a 14 billion parameter model that fit better, by nearly four times. File size does not predict speed. All 103 measured rows are free below, failures included.
Someone asked this morning which models to back up now that NVIDIA is buying Hugging Face. We told people to keep local copies a week ago, and four days ago we wrote about our own disk filling up and breaking our publishing. Both of those are true at once, so here is the version that reconciles them.
Everyone plans their VRAM. Almost nobody plans their storage, and it fails in ways that do not look like storage. A note on the hidden running cost of local AI, including the 591 GB folder we did not know we had and the broken login it caused.
Twenty generators, eight prompts with invented specifics, one shot each, the prompt on every board. New this round: five Krea 2 builds, Qwen Image 2512, a real cloud column priced in Buzz, and a text ladder scored over four extra seeds. Every board at full size, every prompt in all three styles.
A published episode scored 86 failures against its own script. Here is every class of mistake we found making local AI video with LTX 2.5, SageAttention, Krea 2 and ComfyUI, what actually caught each one, and the checks we now run before anything ships.
Two unrelated things happened on the same Thursday. The place almost every open model lives got acquired by the company that makes the chips, and the three biggest chatbots went down together because they share a cloud. Here is what we think it means for anyone running AI on their own machine, including the part where our own pipeline broke this morning.