Two posts in two days say the same thing: RefMods beat everything else for keeping a character consistent in MiniMax H3, and they take seconds instead of a training run. Both are right about the result and the mechanism is not what it looks like, which changes what you should expect it to do well.
On Monday afternoon somebody posted that you do not need the MiniMax H3 character swap LoRA. Thirteen hours later somebody posted that you do. Neither of them is wrong, and the reason why is the most useful thing on the radar this week if you are taking advice about local video models.
Week of 28 September: four AI labs were sued for allegedly agreeing to slow down, three of them then cut their prices, OpenAI paused training after its agents went past what they were asked on US government sites, Alibaba says its model ran its own training loop for a month, a model that never writes a sentence got two open rivals in a week, why Claude’s writing went dense, a law firm bought its own GPUs, and Claude in Chrome stopped opening Reddit.
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.
Someone opened a tab on Monday to try a ComfyUI node pack, came back on Tuesday, and the repository was a 404. Minutes later the author’s entire GitHub account was gone. The model weights it wrapped are still sitting on Hugging Face, untouched. Most people back up the wrong half of their install, and we were doing it too.
Week of 21 September: an AI actress switched into Cantonese on Piers Morgan and her studio’s explanation describes the machine, GitClear measured what AI coding bought, six passing tests certified a planted bug, three labs shipped live voice and none shipped weights, Qwen-Image-2.1 changed its licence, 85.8% of Japanese game developers use generative AI, and RTX 5090s are reportedly going by the pallet.
Qwen released a new image model today at 7.1 billion parameters, roughly a third the size of everything else in the line, with ComfyUI support the same afternoon. Every earlier Qwen image release was Apache 2.0. This one is research and evaluation only, and we read the licence file rather than the thread about it.
Somebody asked today how you count the real cost of AI video once the failed generations are included. We published a 16 minute episode this morning, we keep every take we render, so here are our actual numbers: what we made, what we used, what the retries cost, and the line item nobody prices.
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.
YuE2 landed last week, and what happened next is the best argument for open weights we have seen in a while. Quantised to 8 GB by day two. The missing encoder trained from scratch by a stranger on day five. A LoRA trainer the same day. One thing almost nobody is mentioning, though, and it matters if you plan to earn anything.