HN: https://news.ycombinator.com/item?id=47934437
Reddit: https://www.reddit.com/r/worldnews/comments/1sxzzop/comment/...
Full: https://reddit.com/r/kimi/comments/1v9aqsi/comment/p0cbe0n/
Mirror: https://redlib.us.catsarch.com/r/kimi/comments/1v9aqsi/k3256...
First you spend like 2-3 hours working on a plan, once you have that you just tell the model to go and implement it, do adversarial sub-agent review loops before each commit and also make sure that all tooling and tests pass (including coverage requirements). You do need to poke it in a slightly different direction every few hours, though. Not even any novel work, just some refactoring and SSE notification hardening, bug fixes, alongside environment tuning and getting rid of some bottlenecks (also migrated from Oracle to PostgreSQL but that's mostly done).
That said, Kimi somehow manages to use less context in the main thread than Anthropic's models (even when you use sub-agents and also dynamic workflows in Claude Code), might have something to do with either how the model is tuned or their Kimi Code harness - because even in most of the longer form sessions it doesn't seem to fill up quite as quickly (note: because the kimi vis tool doesn't have a full summary view across all agents, these are the main long running agent stats across some sessions, not sub-agents):
total tokens cache hit rate wall time peak context
283M 98% 3963m 466k
258M 97% 2724m 467k
98M 94% 1353m 393k
67M 97% 614m 434k
75M 98% 1447m 498k
53M 99% 191m 375k
6M 96% 139m 124k
7M 98% 86m 118k
11M 99% 61m 147k
If I feel like the model and I explored a lot of options I won't want to keep context as it might be confusing.
I think the more you use it the better judge you are of whether you should purge, compress, or just keep the context before executing the plan.
I use handoff skill to ask model to write a prompt for itself.
A greenfield project would probably allow at least 2x fewer tokens to be used in most of those long tasks, but I was mostly after consistency and bug fixes along the way as needed.
The model is then given a tool that allows the model to decide to roll back to a checkpoint + a message containing any additional useful information.
It's specifically instructed to use that tool[1] in cases like when it has inadvertendly read a large file where most of the content is not relevant to the task, or after a web search where it's found what it's looking for but most of the content isn't needed, or when it's written code that didn't work as expected, or similar.
It basically lets the model backtrack and "forget" irrelevant details at the end of the context but give itself hints on how it should continue from the checkpoint.
Though, interestingly they seem to be abandoning it in their new CLI (kimi-code), unless it's been folded into other functionality. Not sure if they just feel it's not needed any more with their newer models or if it just didn't work as well as they expected.
[1] named "D-Mail", or "DeLorean Mail" in a reference to Steins;Gate, which again references Back To The Future. See https://github.com/MoonshotAI/kimi-cli/blob/main/src/kimi_cl... and https://steins-gate.fandom.com/wiki/D-Mail
Haven't gone back to it, have been using Claude Code on a private project I'm still architecting.
But yeah, I have no idea about anything about software because you made an assumption off very little to go by.
Doubt these are related, but it made me laugh a little.
Having a lot of active context increases the per-token cost (flops issued and bytes read per token out) so it makes sense to pass that cost on to users. I'm actually surprised it's implemented as a hard cutoff instead of a smooth gradient.
Fewer nodes dedicated to prefill per instance, and fewer nodes in total since you don't need to support a higher KV cache.
Disaggregated inference also means they can tune the balance of compute dedicated to prefill seperately from decode
They did exceed the expecations of pretty much everyone! I've also blogged about using the model, it's a bit on the slow side but pretty good!
> so were totally surprised and overwhelmed by the requests ... or do they just don't have the hardware being in china?
Yes, this is mostly the case: https://x.com/Kimi_Moonshot/status/2078855608565207130
As a user, I much prefer that to service disruptions or severely degraded or secretly quantized performance. However if I didn't have an account, I'd be pretty pissed off about not being able to give them money and become a user.
I was able to press "Join waitlist" and then within 48 hours got accepted. The limits aren't very high, no where near the endless subsided+resets given on ChatGPT/Claude. I recommend ChatGPT for good value output!
Others here mentioned "the providers could be quantizing it!" but some of the providers on OpenRouter have partnered with Moonshoot and OpenRouter shows the int when you expand on the provider.
It should say "mxfp4" but providers like Baseten report FP8.
Kimi had become that popular. I was a subscriber of Kimi back when latest version was Kimi K2. Later I unsubscribed because I jumped over to GLM subscription (they had amazing deal). Now when I wanted to try out Kimi K3 to find out what the fuzz was all about, I couldn’t subscribe to them.
I remember reading a post from Moonshot team about this, they are doing this because they are almost at peak capacity and want to reserve it to keep the quality for their current customers.
We are actually witnessing an open-weight model catching up at catching mainstream users attention. And instead of behaving like Anthropic, they actually care about their users experience.
Who cares? China has always copied and then copied the means of production and then out produced. See also Tesla and now all the Chinese cars eating their lunch.
As long as I get really solid AI models for cheap that do what I need I don’t care if they’re Chinese or otherwise.
I’ll still never use Grok from SpaceX AI cuz eww no, I have principles. ;-)
Is this the exact same model just with less VRAM allocated for context window?
Cheaper?
I usually keep my context in chats below 256k anyways so this would be tremendous honestly.
For pressure at the country level leading to this kind of thing I think it's very unlikely. Here in Sweden it wouldn't just require a vote in the Swedish parliament and before this there'd have to be förarbeten and you can't just brazenly push things through with insane arguments, Swedish social convention goes against it-- and there's just no way to get it through.
It also might not even be legal. "We aren't at war with China and I'm a communist, and the US LLMs are so aligned with values inimical to my political ideology that this is interference with opinion formation" might be an actual legal argument that the ECHR or CJEU might actually have to accept.
I guess it sucks if one wants to expert broadly, but if you're big on vertical integration and the Japanese won't sell I guess you take what you can get.
Of course - Anthropic and OpenAI have an advantage in the amount they can subsidize the usage, but I think those days are waning.