Hacker News Reader

Comment by cogman10 | Hacker News Reader

I've not tried it out, but in the past I've been pretty disappointed in the performance of Kimi models. Deepseek, Qwen, and GLM all appear to perform much better even though Kimi often has higher benchmark scores. Ditto for Mimo.

View on HN

The older Kimi K models (2.5 and 2.6) weren't bad for the time, but all of their models have had problems with overthinking. This also makes them significantly more expensive in practice than their pricing suggests, since they produce way more output (reasoning) tokens than most other models. Anecdotally, I've also had problems with all the pre-K3 models thinking themselves in circles trying to solve very simple problems that other models didn't struggle with. (I haven't played with K3 much because it's just too expensive.)

Same for me, however! Check the price-per-task table. They claim to be cheaper than GLM 5.3.

Edit: or they lie... https://artificialanalysis.ai/models/kimi-k3-1-pro

For me, it is the opposite. It may be slower but it follows the rules better and makes less stupid mistakes, it takes less time to merge the solution.

I have the opposite impression. I find K3 to be extremely capable at full-stack work; its UI design skills are great. I'd love to use it more, but the quota on Kimi's plans is abysmal. I wonder if these new models improve that.

I loved kimi, but had the same issues with usage limits. Now is too late for me to comeback.

Yep, and often actually very expensive to use. More expensive than the frontier models because there's no realistic coding plan.

Reply on news.ycombinator.com