Using an open model feels surprisingly good(matthewsaltz.com) |
Using an open model feels surprisingly good(matthewsaltz.com) |
The smaller/open models are less good at that. But that’s not how software development is done. You don’t prompt a whole app and be done with it. If you’re using it as an aid to traditional software dev, iterating on small, targeted functions, GLM works as good if not better than Claude. Anthropic expects low quality prompts. If you rubber duck GLM, you get absolutely pristine output in most cases.
This has lowered the barrier of entry for many non-SWEs. I'm primarily a data scientist myself in the environmental sector with limited front end development.
My partner proposed an idea to help manage her horses and over the course of several weeks we fleshed out an android app that would enable/assist her with horse care.
I spent a few days in planning mode pointing claude to the services we want to utilise and the functionality.
We now have a fully developed app that we are testing but found several features missing. For example, Claude implement X but without a level of verbosity it failed to implement the edit/deletion of X.
The app is highly tailored to her use case and I had already built the main parts as a POC but she had no user-friendly method to interact with the information she required. Claude made this possible in such a quick time frame that just seems insane. As someone time poor (as most horse people are), it would have taken me a year+ to produce something unpolished when compared to what Claude produced.
I think the issue is that no one is content with incremental progress. We all know one shots are mostly possible, so the age of the personal project is kind of over. There’s no motive to invest dozens of hours getting a working prototype when Claude can give you something right now. So you can’t make small changes until you have that codebase in place already. You’re forced to make sweeping changes if you use AI from the beginning. And it’s not like it matters, there’s no personal attachment to any one part of the code, it’s not even seen!
After open models will also be able to do that, I expect everyone to forget "how software development is done".
But the situations where you need that are narrowing every release. The "Composer 1" era of low-end models is pretty far away now.
The TTFT and tok/s are much higher on the small model so that makes it competitive for a bunch of things. It feels like what old Sonnet used to by the end of last year which is honestly damned good.
What would be useful is a cost metric. I'm curious how much I'd be willing to spend as a premium to not have those companies piping my conversations directly to the NSA. Maybe only some conversations? Claude and OpenAI are heavily subsidized, by all accounts, so Kimi K3 on a private endpoint might end up costing more or less - that's what I want to know.
Now I can't wait for someone to distill K3 into a Qwen 3.6 27b or Poolside S 2.1 sized models for a proper fast local Composer 2.5 replacement.
Harness-aside, I get this feeling sometimes when I swap from a big frontier model to something more nimble like Composer.
I can get into a better thinking and q&a loop with fast models, similar to how I can flow through a file more easily with vim.
If it sounds good it must be good. The code this new model writes is incredible! It told me so!
People need to learn to just post the prompt rather than the LLM output which just fluffs the prompt.
For example, if you modify things at the level of small functions, open models seem to perform just as wel
Making it about the hardware costs is not the play, they’re not an actual barrier.
I can do things like take a photo of a doctor's note among add the appointment to my calendar, send a PDF to my archive tagged, OCR'd etc, search info from internet, look data from Google Maps.
I can even integrate this to home assistant and talk to my agent with my open source Alexa-like system.
In my case, I was foolish enough to run it all on my hardware which is pretty damned fast but has a duty cycle of 5% and runs idle most of the time. It's definitely better done via API.
Tell me more about the Alexa-like system! I have mine at home on a custom OpenWakeWord model trained on the word 'Aurora'. And I, too, have it hooked up to Home Assistant. I have a bunch of Eufy E21 baby cameras mounted on the walls[1] so it has vision through the house. The vision model uses GPT-5.5 on the subscription because I haven't yet set up a Qwen or Gemma multimodal that can see.
With Frigate on my home server I can even watch for events like my daughter waking up! And at night the agent sends out the vacuum if we've cleared the floor of baby toys. I feel this close to the dream of sci-fi AI. Because I auto-forward a bunch of my email to it etc. it knows about what's going on with me.
My wife will sometimes ask the agent information about me etc. and it's way easier to get a fast response rather than waiting for me to see the message etc.[2]
0: https://news.ycombinator.com/item?id=47538158
1: https://wiki.roshangeorge.dev/w/Blog/2025-12-01/Grounding_Yo...
It was truly remarkably easy to build and package it exactly to my whims, in my case as a single docker container with a process reaper that runs llama, my Go code, tts, chat harness, browser in xvfb, and even a mailer daemon. With Gemma, it even runs on a RPi 5.
What’s absolutely wild to me is that over a couple hours, I could probably have it import parts of Home Assistant for my devices directly, and do other wacky stuff in what is essentially software for one.
I can't wait until good enough models can run on affordable hardware.
IMO because they speed-ran it so much (raising orders of magnitudes more, pushing out new stuff orders of magnitudes faster) it will also lead to the rest of the world catching up faster and shrinking the pool of people internal to them who continually benefit compared to what actually went on with IBM. There's only so much upside when you join a company with hundreds-of-billions valuation.
I guess the other part of their business plan bet was "become literal god of AGI". Maybe it'll still happen!
I'm not coding with Claude cause I enjoy the inherent novelty of LLMs. I'm doing it cause it's enabling me to quickly solve problems without getting stuck on the hitches that have deterred me from bothering with dozens of side projects my entire life.
but why?