> I've tried using qwen and deepseek but they can't even output documents

What agent harness did you use? Usually, "write_file", "shell_exec" or similar is two of the first tools you add to an agent harness, after read_file/list_files. If it doesn't have those tools, unsure if you could even call it a agent harness in the first place.

When was the last time you used Qwen models? Their 3.5 and 3.6 models are excellent with tool calling.

You can use GLM-5.1 with claude code directly, I use ccs, GLM-5.1 setup as plan, but goes via API key.

I've been using qwen-code (the software, not to be confused with Qwen Code the service or Qwen Coder the model) which is a fork of gemini-cli and the tool use with Qwen models at least has been great.

You can use both codex and Claude CLI with local models. I used codex with Gemma4 and it did pretty well. I did get one weird session where the model got confused and couldn't decide which tools actually existed in its inventory, but usually it could use tools just fine.

Codex is pretty good at Rust with x86 and arm intrinsics too, it replaced a bunch of hand written C/assembly code I was using. I will try Qwen and Kimi on this kind of task too.

I've been running Opus and GLM side-by side for a couple weeks now, and I've been impressed with GLM. I will absolutely agree that it's slow, but if you let it cook, it can be really impressive and absolutely on the level of Opus. Keep in mind, I don't really use AI to build entire services, I'm mostly using it to make small changes or help me find bugs, so the slowness doesn't bother me. Maybe if I set it to make a whole web app and it took 2 days, that would be different.

The big kicker for GLM for me is I can use it in Pi, or whatever harness I like. Even if it was _slightly_ below Opus, and even though it's slower, I prefer it. Maybe Mythos will change everything, but who knows.

I have used GLM 4.7, 5 and 5.1 now for about 3 month via OpenCode harness and I don't remember it every being stuck in a loop.

You have to keep it below ~100 000 token, else it gets funny in the head.

I only use it for hobby projects though. Paid 3 EUR per month, that is not longer available though :( Not sure what I will choose end of month. Maybe OpenCode Go.

I think it offers a very good tradeoff of cost vs competency

4.7 is better, but its also wildly expensive

IDK about GLM but GPT 5.4 Extra High has been great when I've used it in the VS Code Copilot extension, I see no actual reason Opus should consume 3x more quota than it the way it does

You're probably just holding it wrong.

Do you use Opus through the API or with subscription? Did you use OpenCode or Code?

Maybe a bit misleading. I have used in in two places.

One Is for local opencode coding and config of stuff the other is for agent-browser use and for both it did better (opus 4.6) for the thing I was testing atm. The problem with opus at the moment I tired it was overthinking and moving itself sometimes I the wrong direction (not that qwen does overthink sometimes). However sometimes less is more - maybe turning thinking down on opus would have helped me. Some people said that it is better to turn it of entirely when you start to impmenent code as it already knows what it needs to do it doesn't need more distraction.

Another example is my ghostty config I learned from queen that is has theme support - opus would always just make the theme in the main file

If you view the "thinking" traces you can see why; it will go back and forth on potential solutions, writing full implementations in the thinking block then debating them, constantly circling back to points it raised earlier, and starting every other paragraph with "Actually…" or "But wait!"

Z.ai’s cloud offering is poor, try it with a different provider.

> I've used Claude for many months now. Since February I see a stark decline in the work I do with it.

I find myself repeating the following pattern: I use an AI model to assist me with work, and after some time, I notice the quality doesn't justify the time investment. I decide to try a similar task with another provider. I try a few more tests, then decide to switch over for full time work, and it feels like it's awesome and doing a good job. A few months later, it feels like the model got worse.

I agree - the problem is it’s hard to see how people who say they’re using it effectively actually are using it, what they’re outputting, and making any sort of comparison on quality or maintainability or coherence.

In the same way, it’s hard to see how people who say they’re struggling are actually using it.

There’s truth somewhere in between “it’s the answer to everything” and “skill issue”. We know it’s overhyped. We know that it’s still useful to some extent, in many domains.

What is it that is dogma free? If one goes hardcore pyrrhonism, doubting that there is anything currently doubting as this statement is processed somehow, that is perfectly sound.

At some point the is a need to have faith in some stable enough ground to be able to walk onto.

All people think dogmatically. The only difference is what the ontological commitments and methaphysical foundations are. Take out God and people will fit politics, sports teams, tools, whatever in there. Its inescapable.

I wonder to what degree it depends on how easy you find coding in general. I find for the early steps genAI is great to get the ball rolling, but rapidly it becomes more work to explain what it did wrong and how to fix it (and repeat until it does so) than to just fix the code myself.

[dead]