Experience Using Opencode on the Latest Models
I've been experimenting more with the latest LLM models for coding. And it's pretty impressive how far things have come, and how these tools are pretty impressive.
I've mostly been using the Kimi 2.5 model with Opencode as the coding agent. I still find that mix pretty great. I think the whole vibe coding/AI assisted programming workflow that Opencode and similar encourage might not be the best for quality code, but it is pretty addictive seeing that type of rapid progress. Until you get to the very highest (expensive) tier of Claude/Anthropic and OpenAI models, Kimi performs basically on par or better than what the biggest companies offer.
And these coding agents can take care of a lot of the boring drudgework of programming. They are good enough right now that I don't have to spend too much time manually intervening and fixing what the LLM did — these tools are getting pretty accurate.
I've spent many hours working on a project, tweaking it back and forth, with the main thing stopping me from spending even more time is the fact that I have to pay for the credits to run inference for the models. Once you spend the time working through all of quirks these tools have gotten pretty smooth as far as workflow goes. It's genuinely fun to do this on the recent LLM models that have come out.
Cost right now is the only real problem, these things will burn through tokens by the millions. It's pretty clear that the $20/mo for coding agents tier from OpenAI etc (even though the limits are being tightened) are being subsidized pretty aggressively. When you compare the amount of time you get on a coding agent from such a plan vs what open source alternatives cost, OpenAI etc can't be making money from the coding agent offerings. On the other hand, it's probably cheaper to use a self hosted frontend (OpenWebUI etc with a hosted inference API) than it is to pay for a paid tier of ChatGPT.
I've also noticed that Opencode and other open source agents/frontends are very sensitive to token output performance. Using a somewhat more expensive inference provider that provides fast performance will improve the experience quite a bit. Switching API providers basically fixed some of the issues I was having with the model freezing etc.
The project I've been working on as part of my testing is this https://git.selfhosted.onl/theo/marginleaf
It's a personal blogging CMS. It can do the typical blogging engine things, but instead of a frontend editing interface, I created an API, and I built some tools that allow me to fully manage it from Open WebUI, which opens some pretty neat possibilities. It feels like a somewhat interesting possibility to have some of these chat tools getting good enough that they can be the main interface with an application — instead of a more traditional web UI.
In particular, the Open WebUI tools can be found here https://git.selfhosted.onl/theo/marginleaf/src/branch/main/openwebui_tools
But mostly I created it because it's fun to work on that type of thing.