Kimi K3: Open Frontier Intelligence

Post by panting » Fri, Jul 17, 2026, 6:42 AM UTC

vl wrote: post #581

softwaredoug wrote: post #478

So Chinese labs are driving essentially towards commodotized intelligence. Even if its a few months behind the US. Is this a classic 'commoditize my compliment' situation? They want to sell the hardware and infrastructure behind AI and make the software part not the value driver / moat? I can see it. But also even two Chinese labs sinking 100s of millions USD into training isn't exactly commoditization. It's still a…

This is strategy by Chinese government, so much of US economy is invested in AI. Releasing free or cheap versions of the models undermines US economic growth. It’s asymmetric strategy that makes sense if you are close second in AI race. If situation is reversed, US would do the same.

Post by i5heu » Fri, Jul 17, 2026, 6:49 AM UTC

Gecko4072 wrote: post #419

api wrote: post #415

Earlier quoted context omitted.

I had a thought a while back: sell large local models burned onto fused compute / ROM chips. Like cartridges for old game consoles. Slot (or probably plug into USB-C) and go. It’s an ASIC with the model wired into it so it’s very low power and fast. I’d buy these. Say $100 for a frontier class model. Maybe more.

This would be very compelling. Can anyone share more details on how it would work? Only issue is that you are stuck at a certain point in time but that’s not a huge deal. Even just a good 27b model would be useful.

Post by [deleted] » Fri, Jul 17, 2026, 6:55 AM UTC

katzenversteher wrote: post #736

pitched wrote: post #725

Earlier quoted context omitted.

An approach I like to help solving this is antagonistic or review agents. The first agent decides that eye glows turn NPCs into enemies, the second agent is fully dedicated to deciding if that is valid. If the review fails, it leaves notes and the original agent tries again.

So far I only tried it with a single LLM in the dungeon master role. Your approach sounds promising (and I will definitly try it) but also a bit like a complicated workaround. What I mean: In games with humans the dungeon master is usually one person, not a whole council ;)

Post by versteegen » Fri, Jul 17, 2026, 6:59 AM UTC

eckr wrote: post #321

meetpateltech wrote: post #281

Kimi K3 blog is up: https://www.kimi.com/blog/kimi-k3 2.8T param open model, 1M context, native vision. Weights releasing by July 27 with technical report. Launching with max thinking effort by default; low/high effort modes coming in future updates.

These benchmark numbers are insane. The days when China was 6 months behind are over? How are they doing this with so much less resources than the US??? I have so much respect for the researchers there

  Kimi K3 beats each model (out of 35 benchmarks, excluding missing):
  vs Fable 5           : 12/35 (34%)  (ties: 1)
  vs GPT 5.6 Sol       : 19/34 (56%)  (ties: 1)
  vs Opus 4.8          : 30/35 (86%)
  vs GPT 5.5           : 30/34 (88%)  (ties: 2)
  vs GLM-5.2           : 19/19 (100%)

Post by avereveard » Fri, Jul 17, 2026, 7:05 AM UTC

katzenversteher wrote: post #718

simonw wrote: post #111

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.

Hey Simon, I noticed one thing all LLMs are currently pretty bad at and maybe we could create a benchmark from it. Let an LLM play the role of a dungeon master and tell it to strictly stay in the script/story and only allow realistic player actions. You will notice that they are easily brought off track. E.g. - Tell the LLM that you as a player noticed a strange glow in an NPCs eyes -> the NPC becomes an enemy. - In…