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

And that’s not even all of it. Basically they break models in many ways, and they’re slimey Tech Bros.

LM Studio is better, and easy.

If you’re on Nvidia, and want to run optimally, I would use the ik_llama.cpp fork. On AMD, regular llama.cpp. On a Mac, use an MLX runner (Like LM Studio) with an MLX quant (ideally an MLX-DWQ quant).

It’s all pretty technical, and… thats kinda the point. LLMs are just too performance sensitive and too finicky to not have a grasp of how they work. There is no "easy button" to run them without bad results, there can't be.

But if you don’t have time for that and just want to see if it’s worth it, I’d suggest self hosing your own UI, and trying the dirt cheap APIs of models you can theoretically run on your setup. This will give you a “best case” taste of what they’re capable of.

Oh, and I just saw you have a 3090.

To get more specific, you can actually run way better models than Qwen 3.5 and Deepseek coder (both of which are very obsolete now). The best that's practical depends on how much CPU RAM you have, but at the minimum you can do Qwen 3.6 27B, with a more optimal quant like ones here: https://huggingface.co/ubergarm/Qwen3.6-27B-GGUF/tree/main

Or Gemma 31B QAT: https://huggingface.co/unsloth/gemma-4-31B-it-qat-GGUF

If you have 128GB CPU RAM, I can upload my custom MiMo 2.5 quant. That should "beat" the cheapest Claude, give or take.

If you have 64GB, I'd suggest a quantization of Step 3.7.

If you have 32GB or 48, I'm not sure. I'd need to look if any "small" MoE is actually better than Qwen 27B now.