Comment by realusername
7 days ago
> If this is really their moat then the Chinese companies will win.
I already switched to a Chinese provider personally, I don't think the difference between both really justifies the wide gap in pricing
7 days ago
> If this is really their moat then the Chinese companies will win.
I already switched to a Chinese provider personally, I don't think the difference between both really justifies the wide gap in pricing
> I don't think the difference between both really justifies the wide gap in pricing
I'd be ecstatic if this was true, but nothing so far comes close to the SOTA models from OpenAI + highest reasoning, but I'd be more than happy to be proven wrong by testing it out myself.
So far, I've tried MiniMax M3, GLM 5.2, Hy3, MiMo-V2.5 (+ Pro), DeepSeek V4 Pro (+ Flash), Gemini 3, Kimi K2.6, GLM 5, all the various Qwen variants and probably a bunch more I forget about, in a wide array of harnesses (Codex, pi, opencode, my own and more), and still nothing seemingly comes close to GPT 5.5 (now 5.6) xhigh for tasks beyond 5-10 minutes of work, they all more or less collapse after a while in my experiments. Although most of those do work well for really tightly scoped tasks.
What specific model are you thinking about here, in case I've missed testing it?
I'm using Kimi 2.7 and GPT 5.5 at home, Opus (4.8 I think) at work and I really don't see much difference honestly.
Sure, Claude might be 90% correct and Kimi only 70% correct but does that matter when 90% isn't enough to make it work autonomously anyways?
My workflow is just strict supervision of what's happening, I also edit the agents file with anything I see the model doing that I don't like.
My sessions are also short, after any task which is completed, I just kill the session and start a new one so I don't think I have more than 15 min sessions unless it's tech discovery.
> Sure, Claude might be 90% correct and Kimi only 70% correct but does that matter when 90% isn't enough to make it work autonomously?
Huuh, what does this mean? GPT models frequently do 100% of what I tell them to do, anything less and I'd see no point in using agents for work at all. Do you tell them stuff then 30% of the cases Kimi goes off and does other things, or what do you mean? The time the agent does something unexpected, I can almost always trace it back to me fucking up something in the user prompt, or the system prompt being wrong somehow, I'd lose my mind if it was only "70% accurate".
> My workflow is just strict supervision of what's happening, I also edit the agents file with anything I see the model doing that I don't like.
Same, including inspecting exactly what the (full verbatim) sent system/user prompts are, which the change we're all discussing here is getting in the way of.
But "Kimi only 70% correct" sounds like it's so bad it's not worth using. In my testing, I didn't find that the model just went out and did other things, but all the providers I tried were way slower than even Sol which is kind of slow to begin with, and it's really inefficient with it's thinking. Tasks that took Sol five minutes could take 15 minutes with Kimi for example, which just feels like such a waste too.
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