dirkg
Joined 10 years ago
Joined 10 years ago
Can someone comment on ghostty vs wezterm? both are very popular, wezterm is much more configurable due to lua scripting, I suspect performance is going to be identical and not measurable by humans.
the value of local models is allowing normal people to access AI without needing to subscribe to cloud services. this is esp imp for the rest of the world where even a 12GB gpu is extremely expensive.
there is no real viable local option that will come even close to Sonnet/Gemini Flash or the cheaper chinese models. Even if your pc costs <$2k you are never going to recoup the hw costs, and the results will be far worse.
you can run qwen 3.6 35BA3B on a 12-16GB vram gpu and ot works pretty well.
https://www.youtube.com/watch?v=8F_5pdcD3HY&t=1s
even the 27B in some quants can fit.
https://www.reddit.com/r/LocalLLaMA/comments/1tkmgwj/qwen27b...
qwen IMO is far better for coding, esp agentic coding when combined with something like Pi, it comes probably close enough to Sonnet for a lot of use cases.
Gemma family is better for almost all other tasks you'd use a local llm for.
AWS has much bigger mindshare, thats it. Google has a well deserved reputation killing products, but their actual products/APIs are so much nicer.
Haven't used Azure but I bet its much better integrated as well.
when I hear people complain about these projects it just sounds like hypocrisy.
I've always wondered why someone doesn't just bundle a nice looking shell prompt with common nerd fonts and make it the default in a single package you can install.
e.g. Netflix/YouTube
Cue endless debates about how Vim is the best ever ...... I'm sick and tired of everyone telling me that their neovim setup with a tiling window manager with million customized rc files is somehow better than vscode with a mouse (which mind you still has plenty of keyboard shortcuts) with sane windows. /rant
With their massive codebase and already deep investment in AI/ML, I'm pretty sure Google and likely MS already have the ability to do massive refactoring, validate it using tests, reiterate, train, rinse and repeat.