571–580 of 1001 posts
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What is plausible is that they haven't made any attempts to explicitly steer certain opinions into a certain direction, and just let the model take over the bias of the training data, whatever that may be. Filtering in the front end is the easy, lazy way out to be legally compliant.
My testing prompt for these models is by no means objective or repeatable (like the pelican) but it's a nice test of curiosity: > Impress me with a 1 page html file Result: https://ydaurtg3fdwhq.kimi.page/ Came out looking pretty cool! By contrast, Fable produced a moderately more interesting "live observatory" of the solar system.
Just like you I am super impressed by Kimi K3.
I do a qualitative benchmark series making 3D explainers and so here's Kimi K3 vs Claude Fable:
https://generative-ai.review/2026/07/kimi-k3-rush-test-vs-cl...
I've put links to the posts on GLM5.2, Opus 4.8, Chat GPT 5.5. I grab video screencaps so you can compare in detail. The full interactive Kimi output is at the bottom of the post if you want a comprehensive 3D play around
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it also undercuts American dominance, which is something China is always happy to invest in, even if it doesn't immediately mean Chinese dominance
This. More people should read Simon Wardley. Also China's silent but powerful support of Russia and its invasion.
Pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... - rendered via the OpenRouter API: https://openrouter.ai/moonshotai/kimi-k3 95 input, 16,658 output = 25 cents! https://www.llm-prices.com/#it=95&ot=16658&ic=3&oc=15 (13,241 of those were reasoning tokens.) I think that's the most expensive pelican I've rendered through a Chinese model so far.
Wrote this up in a bit more detail on my blog, including some thoughts on what value the pelican benchmark can still provide here: https://simonwillison.net/2026/Jul/16/kimi-k3/
Try setting reasoning levels yourself manually. We see in the benchmarks that one of the graphs shows low, mid, max, so its clearly there.
I had the same issue with GLM 5.2 only offering high/max.
By playing around with openai compatible protocol, and setting the reasoning level from none, low ... high, xhigh and testing a flawed logic test.
It was easy to see that GLM had all the different reasoning levels. Low was like one line, medium did a few, high started to really expand, xhigh was a page or 2, max was MAX.
Very sure that you can force K3 into using less reasoning.
I'm expecting Anthropics reply soon though.
It would be trivial for them to distill Mythos.
Pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... - rendered via the OpenRouter API: https://openrouter.ai/moonshotai/kimi-k3 95 input, 16,658 output = 25 cents! https://www.llm-prices.com/#it=95&ot=16658&ic=3&oc=15 (13,241 of those were reasoning tokens.) I think that's the most expensive pelican I've rendered through a Chinese model so far.
https://canada.newark.com/productimages/large/en_US/4492516....
In the field I work in, if someone says "Pelican", 99.99% of the time it's going to be an equipment case. We never have reason or need to refer to the actual bird.
My testing prompt for these models is by no means objective or repeatable (like the pelican) but it's a nice test of curiosity: > Impress me with a 1 page html file Result: https://ydaurtg3fdwhq.kimi.page/ Came out looking pretty cool! By contrast, Fable produced a moderately more interesting "live observatory" of the solar system.
Nice qualitative test! Just like you I am super impressed by Kimi K3. I do a qualitative benchmark series making 3D explainers and so here's Kimi K3 vs Claude Fable: https://generative-ai.review/2026/07/kimi-k3-rush-test-vs-cl... I've put links to the posts on GLM5.2, Opus 4.8, Chat GPT 5.5. I grab video screencaps so you can compare in detail. The full interactive Kimi output is at the bottom of the post if you want…
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I would also assume the same for non-Chinese as well
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> its overall intelligence ranks second only to Claude Fable 5 and GPT-5.6 Sol Pretty sure ranking “second” to two others means ranking third.
While you are technically correct, in English it’s perfectly fine to say it this way as well. “Second only” here has meaning “next after”, not “number two”.
England is second to none.
Just in case you were thinking of signing up directly with Moonshot to use the service, they appear to train even on API use: > We may use Content to provide, maintain, develop, support, and improve the Services, comply with applicable law, enforce our terms and policies, and keep the Services safe and secure. Customer who requires restrictions on the use of Customer Content for training or improving Moonshot AI mode…
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