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

Almost exclusively Fable at xhigh. I sometimes run out of tokens, but most weeks it's not a problem. The limiting factor is by far how fast I can push understanding of what was made into my brain, and I find that I waste time using Opus. It makes annoying mistakes, and it makes assumptions that are often wrong instead of actually verifying. And it can't write so I can understand it.

I have “unlimited” (but metered) tokens at work. I was primarily a Claude (Opus and Fable) user until Astra came out.

Astra’s outputs are much more concise while being similarly accurate, they seem more information dense. It’s also extremely fast and doesn’t have to “go check instead of answering from memory” if the answer is already in context, or dig super deep into a project before answering.

It’s honestly refreshing to work with Astra after being basically burned out from reading Claude’s responses.

It’s not perfect. It’s just as “mid” for professional SWE work as Opus/Fable, regularly making incorrect assumptions/generalizations, requiring steering in large codebases, and being incapable of making reasonable long-term software design decisions on its own in complex projects.

I'm coming up on a month with my 2x GB10 cluster. I was at 1x for a week before I pulled the trigger for the second.

Initial setup was a tad annoying because I had to update their firmwares and then power cycle them to get the 200GbE link working at full speed. After setting that up, it has been pretty smooth. I don't directly deal with the cluster, usually I just have the LLM itself handle updates/stopping to load different models.

Generation speed and TTFT is decent with Qwen3.8-flash, and it does a good job for my fiddling around with enough concurrency for multiple sessions/subagents. GLM 5.3-flash was also nice, but not too much better for how much slower it is.

I should also add that I already maintain a homelab with a couple of computers, VMs etc, so I am probably somewhat more tolerant of the occasional issue and fine with manually managing stuff over SSH. I think this is just a tradeoff of self-hosting relatively recent tech though.

I have a triple 3090 rig, but it mostly stays powered off because of the massive power draw and cooling requirements. The Sparks are slower but at peak they consume as much power as my 3090 machine at idle.

The recent talk of regulation has me wanting to pick up 2 more Sparks, but that's mostly to have the capacity to play with multiple models, local model tuning and to be ahead in case they force some limits/registration requirements for buying new hardware (kind of like the attempts to regulate 3d printers).

Whatever is the default in Codex CLI.

> Me too. Claude Opus 5's English is insufferable. Opus 4.6-4.8 was more reasonable.

I suspect this degradation is happening because the AI labs are using the LLM's output to feedback into the input, to create a thinking loop, and they're optimizing that.