I currently use DeepSeek-V4.1-Flash and the V4-Pro and -Flash versions before that, because they are extremely cheap. I have spent less than $25 for over a billion token so far (1B cached, 15M out, 19M in). I even prefer the DeepSeek models over the older OpenAI offerings. When I tell a GPT-5.x model to do some difficult task, they often give up saying it can't be done, or cheat by modifying the tests, while the DeepSeek models are more persistent and less prone to cheating.

GLM-5.3, GLM-5.3-Flash and Kimi K3 are also fine, but slower, more expensive, and less good for what I use them for, which is mostly Python and CUDA programming with some JS and HTML inbetween.

But almost all of my tasks are verifiable tasks, which means that the LLM can check whether it is done or whether it needs to keep trying. If you are mostly working on problems where the quality metric is based on vibes, YMMV.

I haven't tried Astra or Fable yet, because I am not made of money and am happy with my current setup. Also, the Opus models' writing is absolutely insufferable. My blood pressure rises every time I see a Claude-generated slop README.