Kimi K2.6 Wins Praise From Power Users

Hot take: this is a user-fit story as much as a model-quality story, and the biggest signal is not raw intelligence but how well Kimi matches a heavily tuned workflow.

• –The post is an anecdotal comparison, not a benchmark, so the strongest claim is about perceived usefulness in real work rather than objective superiority.
• –The user’s process matters: they invested hours into custom instructions and memory-style correction loops, which likely amplified Kimi’s performance.
• –The main upside described is practical reliability for writing and methodical workflows, with lower frustration and less prompt babysitting.
• –The main downside is vendor dependence: the user worries about model updates breaking behavior and about being unable to run the model locally.
• –The comparison is emotionally charged and includes broad attacks on other model vendors, so the editorial value is in the product experience, not the rhetoric.