[walrus01]

Quoting from the article:

> In our runs, K3 served 16 concurrent sessions (GLM-5.2 managed 24). Aggregate token throughput is about 30% lower (122 vs 170 tok/s at 16 users), and median task time is about 50% longer (38 vs 26 minutes). That makes K3 roughly 8 times slower than our Claude Code baseline. However, K3 makes up for it in quality, resolving 86.4% of tasks, 24 percentage points above both GLM-5.2 and Opus 4.8 (62.5% for both).

I think there's some less tangible advantages to self-hosting something on the scale of Kimi K3 that can't be quantified in a specific number like token/s or percentage of problems solved. Such as:

a) data privacy/sovereignty from a wide range of possible perspectives, from medical to personal to "we can't have our data go to the USA" for some Canadians and Europeans.

b) being able to give it information security/network security tasks and red team scenarios without triggering claude or openai refusals.

c) being able to give it information security/network security tasks with zero risk of getting your account banned or investigated by anthropic or openai.

[personjerry]

why are information security / network security tasks bannable?

[walrus01]

You'd have to ask Anthropic or OpenAI, but I've seen probably more than a dozen reports of it happening. You also risk getting your account banned for discussing certain risky things in chemistry, biochemistry, weapons, conflict, terrorism/history of guerilla warfare.

I imagine that within Anthropic and OpenAI there is a huge data set of "big no no!" topics that they maintain and continually add to. For alignment training and for more blunt purposes. For instance ChatGPT 3.5 could be instructed, as satire, to write a press release in the style of the English language propganda arm of ISIS but they put a stop to that fairly quick.