If open weight models are the future, U.S. AI companies are going to have a hard time

I ran DeepSeek and Llama and Mistral at home on my consumer grade gaming PC.

With a little tweaking of the system prompts and configuring web search, I was running a local LLM that felt pretty darn close to the commercial LLMs.

With this technology out in the open internet where you can download the models in a few hours I don’t see how the commercial AI companies are going to last. If selling “Artificial Intelligence” subscriptions is all your company does for revenue, you’re screwed.

I downloaded and ran an LLM that I could have a conversation with and feed basic coding problems to for basically zero dollars and ran it on my puny gaming machine…puny compared to enterprise-class hardware. It would be trivial for a company with a very moderate budget to buy some servers and start running their own LLMs that they can use to feed all the PII and HIPPA data they want.

And Llama and Mistral are ancient history at this point.

The cutting edge of local is lightyears better now. It’s basically where ChatGPT/Anthropic were not that long ago, with a bit less world knowledge because of the size.

What’s the cutting edge now? Skool me…I want to try it. Can I grab one using ollama?

sleepingrobots.com/dreams/stop-using-ollama/

And this is just the tip of the iceberg for ollama. They’re the same kind of scammy tech bros as OpenAI.

The best setup depends on your hardware. There is no “easy button” unfortunately, quantized LLMs are just too intense and finicky to run without making some informed choices.

It also depends on what you want to do with the LLM. For example, some are too slow or bad at long context for agenic use, some quantizations are great at scripts but terrible outside that, or vice versa.

But LM Studio and Qwen 3.5 35B Q4 is probably the “easiest” flat recommendation I can make.

Or… honestly, just pay $40 for basically unlimited usage for a year from an API, then roll your own frontend.

Well that sucks. I was really impressed as a novice to open weight LLMs with the ease of use for Ollama on Bazzite.

I’ve been running LM Studio on Bazzite and I had to do nothing to get it working. Just go to the LM Studio website and download the .appimage for Linux. If you open it with Gear Lever it will install like an app from the app store and show up in your launcher with an icon.

From there I have just been able to download models and use them from in the app. In fact I setup a local server to connect to my IDE and have been trying out local models for coding. It’s pretty cool

Awesome! I’ll give it a try.

I can also vouch for lmstudio. If you can get Hermes running on Linux I would suggest trying that as well. It connects to lm studio and you use Hermes to communicate with the model. Iook into it as there’s a lot to it, I’ve really been enjoying using it so far it even learns how I like to create tasks and I’ve stopped having to ask it to delegate certain tasks, it just knows to do it and to break down the tasks so my fairly context starved local model can handle it.

As for a model, the Qwen 3.6 family of models do really well. I’d suggest the Qwen 3.6 35B a3b probably Q4 depending on your hardware. It’s large, but because it’s a mixture of experts model only 3b of experts are kept on vram at any one time so it stays fast. Qwen 3.6 27b is the smarter “dense” model, but trying to stay with Q4 for quality it becomes too large for 16GB vram and for me runs at like 2 tokens per second lol

+1 for Hermes.

If you have a newer Nvidia GPU, you can run Qwen 27B via exllamav3 and get good quality/speed in 16GB. And it’s worth the trouble, as 27B is an amazing model.

If it’s AMD, yeah, a3B is a good bet, depending on how much spare CPU RAM you have.