Ask HN: What default model do you use and why?

Gemini 3.8 + antigravity. Opus also in antigravity for harder stuff.

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.

It really depends.

For high-level strategic conversations, I use Fable.

For planning, I use Opus or Sol. Sol is generally preferred; it’s faster, cheaper, and less verbose. But I still find Opus more capable on the most nuanced or complex tasks.

For planned implementation, I use Sonnet.

For one-shot unplanned implementation, I’ll use whatever model seems best for the task. FWIW, I’m increasingly turning to Grok here.

I use Luna all over my workflow for reporting.

I use all of em, ChatGPT 5.6luna ion web, for quick tasks(without signup), (ii personally feel ChatGPT isn't straightforward especially when quizing its opinion on a topic) , Gemini for academic work to encyclopedia and know-how discussions, recommending solutions to technical tasks by looking up web for me(it's my primary driver, but lags behind in coding abilities,its large context is a plus. I recently started returned to claude and it isn't bad, since I'm not a paid user... So i don't have a personal assessment on newer models capabilities.

Grok is keeping up and really good at explicit stuff, i think that's a drawdown for me. I think most nsfw was made with grok

As for meta ai, i feek it's a total joke, i don't have access to muse cause meta has decided not to support older OS versions (I'm on Android).

This comment box makes me feel almost as if I'm coding, because of the font. Pretty noice

Given that Fable is the only one that fucking listens to me and writes proper Go code, that’s what I use for everything code-related. At least on my personal projects.

If I don’t care about the code, i.e. I’m writing something quick just to test something, I’ll use GPT Astra to save my Fable tokens. For conversations and research I usually go with GPT Astra Pro.

For Home Assistant I use a combination of Grok 4.20 and DeepSeek Flash 4.1. Grok as a voice assistant, because it’s the only model with good latency here in Brazil (it’s nearly instant), and DeepSeek for everything else.

I don’t really use LLMs for writing, but I’m writing a fiction book on the side, and when I tried to use one for ideas, Gemini Flash 3.8 gave me the closest to good writing out of the ones I tested. Not enough for me to use it for the task, though.