Good point, I worded that incorrectly and should have been more specific. OP trained an LLM from scratch, but it's GPT-2 and with even worse performance than the GPT-2 which OpenAI shipped a few years ago.

I can't edit it now, but OP did not train a useful LLM from scratch. In editing for clarity and tone I think I omitted that away. Somebody searching for a reproducible way to produce a usable model on their own 3090 won't find it in this post. But someone looking to learn how to produce a usable model on their own 3090 will be educated on their post.

"Not a useful LLM" is not a knock on the OP! This is an _excellent_ educational and experiential post. It includes the experimentation with different models that you'll never see in a publication. ANd it showcases the exact limitations you'll have with one 3090. (You're limited in training speed and model size, and you're also limited in how many ideas you can have cooking at once).

The "experiment at home, train a model, and reproduce or fine-tune on someone elses better GPU" is tried and true.

(Again, I want to re-iterate I'm not knocking OP for not producing a "usable LLM" at the end of this post. That's not the point of the post, and it's a good post. My only point is that it's not currently feasible to train your a useful general-purpose LLM on one 3090.)

If you just want to run a local LLM you could download ollama and do it in minutes. You'll be limited to small models (I would start with qwen3:1.7b) but it should be quite fast.