Wow. So kimi is suddenly half the price for all users until they hit 256k of context? Thats massive.
I don't think so. This is a separate model, so I assume that if you just use this and switch to the 1 million context model when you reach 256k, your cache will be invalidated, so you'll re-pay the 256k tokens on the 1 million context model pricing.<p>Edit: I was wrong, thanks to longwave for pointing this out. It's absolutely possible to start out on the 256k model and then switch to the 1 million model when you get close to the context limit without invalidating the cache:<p><i>"When switching from k3-256k to k3 (1M), if k3-256k is close to the 256k limit and you don't want compact to lose information, you can switch directly to 1M. The current version switching from 256k to 1M does not affect the cache."</i>
As far as I understand, no. They're suggesting that smaller context windows are typically cheaper (fewer input tokens over time).
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This seems functionally similar to OpenAI having a step in pricing once you exceed a certain context length (also at 272k aka 2^18 aka 256k).<p>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.
RAM needed for keeping KV cache around may be the more expensive factor.
Not surprising it's a hard cutoff: they almost certainly have two infrastructure configurations for the two max sequence lengths<p>Fewer nodes dedicated to prefill per instance, and fewer nodes in total since you don't need to support a higher KV cache.<p>Disaggregated inference also means they can tune the balance of compute dedicated to prefill seperately from decode
This is just an API level change right? The model itself should be the same I think.
> k3-256k is now available. Within 256k context, it delivers the same results. k3 (1M) consumes about twice as much quota as k3-256k.
This isn't quantized, right? Just a smaller context?
i've never had any issues with 256k context. see no reason to bump up to 1m if it comes at a premium.
Hopefully this helps reduce some of the pressure on their infrastructure. Their models have all become super dumb recently and their support are not addressing it. I have a hunch they’ve been serving a significant percentage of requests with quantised models.
Since Claude is the first time for me really, really out (TIL against my wished about <a href="https://status.claude.com/" rel="nofollow">https://status.claude.com/</a>), I am now interested enough to see what else works. But ... when I click pricing, I see "Join a waitlist". Wtf? Are they really that good, so were totally surprised and overwhelmed by the requests, is this a marketing stunt, or do they just don't have the hardware being in china?
> Are they really that good,<p>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!<p>> so were totally surprised and overwhelmed by the requests ... or do they just don't have the hardware being in china?<p>Yes, this is mostly the case: <a href="https://x.com/Kimi_Moonshot/status/2078855608565207130" rel="nofollow">https://x.com/Kimi_Moonshot/status/2078855608565207130</a><p>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.
Since the model is open-weights, you can get from other providers, for example see <a href="https://openrouter.ai/moonshotai/kimi-k3#providers" rel="nofollow">https://openrouter.ai/moonshotai/kimi-k3#providers</a>
Do any support the smaller context for better pricing?
The only downside with third party providers is that you have to trust that the provider have setup and configured it correctly, and is not secretly quantizing it.<p>See Kimi Vendor Verifier.
Not at all a marketing gimmick, the demand is simply that high.<p>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!<p>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.<p>It should say "mxfp4" but providers like Baseten report FP8.
No, the waiting list is true.<p>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.<p>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.<p>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.
It's an extremely popular model hosted by a company affected by hardware export bans. I doubt they'd voluntarily prevent people from subscribing if they didn't absolutely have to to maintain service quality.
Codex uses 256k masterfully, 1M is luxurious but still quite expensive and seems not necessary as a default.
That's because it has the best compaction of anyone, and it's not even close.<p>Claude might as well not even do it in my experience.
> Codex uses 256k masterfully<p>This.<p>When working on hard problems (not "vibecode me a script to show an alert box", but e.g. "let's see what this three-level LUT-state-machine obfuscated binary does"), hitting the 1M (!) context window with Claude Code feels like you were talking to Claude Claudewski when his shift just abruptly ends, he packs his things, throws the office keys at Claude Claudeson in-between the front door frame while handovering like "Hi! Nice to see you, good luck." and now here we go again, you are working with someone who just experienced an acute amnesia. It tries everything it already tried, everything it was told in the initial prompt to not do, everything it was told in follow-up prompts not to do. "You were right, this approach does not work and we don't have 20 TB RAM on this machine for full symbolic execution, let me try..."<p>In Codex, it's so seamless that I sometimes just notice "wait, the context was 20 % remaining, it is 70 % now, wow, when did this happen", while it seamlessly works on the task. Basically never had an issue with context on Codex, be it coding features, cracking hard crack-me ciphers, or researching basically anything.<p>(For full disclosure, my last experience with Claude was a few weeks ago when I cancelled the subscription, maybe they fully reworked the traumatic "Summarizing" - "Oh, hi! Where are we? Who am I? What we are doing? This is taking too long, let me take a shortcut..." lobotomy they were doing in the meantime.)<p>256k is enough when the harness uses it properly and the model is not stupid. And also when the tokenizer is not tuned to invoice as many tokens as possible...
Needing large context windows is an illusion.
I'll have to give it a shot some time soon. I just can't imagine working on any of my serious projects doing a new large feature with that little room. By the time it has looked at half the code required to start planning the work, it'd be out of context. Must use sub agents better or something.
Also, a token means something different in each model/tokenizer. "For improved performance we will use (read: invoice you) 30 % more"...<p><a href="https://platform.claude.com/docs/en/about-claude/models/whats-new-sonnet-5#new-tokenizer" rel="nofollow">https://platform.claude.com/docs/en/about-claude/models/what...</a>
That's actually nice! I usually try to stay below 200k context anyway.
This exact same comment is the top comment on the reddit thread for this news<p><a href="https://www.reddit.com/r/kimi/s/BFa1TR9vNg" rel="nofollow">https://www.reddit.com/r/kimi/s/BFa1TR9vNg</a>
I searched one other comment of theirs in their history and see the same thing. On mobile so I can’t easily tell if this account is the bot account or if the ones on Reddit are.<p>HN: <a href="https://news.ycombinator.com/item?id=47934437">https://news.ycombinator.com/item?id=47934437</a><p>Reddit: <a href="https://www.reddit.com/r/worldnews/comments/1sxzzop/comment/oiqkl33/" rel="nofollow">https://www.reddit.com/r/worldnews/comments/1sxzzop/comment/...</a>
Does that URL link back to you somehow?<p>Full: <a href="https://reddit.com/r/kimi/comments/1v9aqsi/comment/p0cbe0n/" rel="nofollow">https://reddit.com/r/kimi/comments/1v9aqsi/comment/p0cbe0n/</a><p>Mirror: <a href="https://redlib.us.catsarch.com/r/kimi/comments/1v9aqsi/k3256k_is_now_available/p0cbe0n" rel="nofollow">https://redlib.us.catsarch.com/r/kimi/comments/1v9aqsi/k3256...</a>
For me the sweet spot is somewhere under 500k depending on how extensive I want to get. You can build up a sizable effort project in half a million tokens with Claude, with Claude having all the context from ground 0 to wherever you're off at.
"256k ought to be enough for anybody"
LLMs is quickly became commodities. US AI labs like OpenAI is losing their moat. Hyperscalers and data center owners who can sell cheap token will win
I believe Codex harness is pretty sticky though I haven’t tried many others. Does anyone else provide a harness of that quality?
Pi harness with subagents is pretty great. I’m using it for everything now.
Their harness is indeed nice, but we're using it against our own AI Gateway at work. Right now we only expose GPT models on it, but I imagine it's possible to add our own models eventually
opencode is highly regarded, I use it exclusively
I have so much gratitude to the frontier companies who did all the extremely complicated research and development, model by model. It already feels difficult to remember how much capital it really took. Thank you for getting us to this point.
Not relevant to this link but I was thinking about the allegations of Chinese AI companies distilling from the big frontier American ones. And I came to the conclusion: I don’t care.<p>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.<p>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.<p>I’ll still never use Grok from SpaceX AI cuz eww no, I have principles. ;-)
This is a fantastic option for swival.dev given its very efficient context management compared to e.g. Claude Code.
Can we assume that model performance at 90% of the 256k limit != 90% of 1M token limit?<p>Is this the exact same model just with less VRAM allocated for context window?
What is the purpose of this? Just a hard cutoff below the actual context window? You could set that in your harness anyway.
At least in the self-hosted LLM inference engines, you have to pre-allocate space for the maximum amount of context you want to allow for each parallel session. By using a lower maximum, you don't have to allocate as much VRAM for each session, allowing more usage for the same amount of hardware. Thus, cheaper.
Uses less quota (i.e., cheaper). For people who like to keep their contexts small, this is a no-brainer.
> k3 (1M) consumes about twice as much quota as k3-256k<p>Cheaper?
I can't seem to find pricing for this model. Since the context size is just a quarter of the full size K3, is the price also much cheaper?<p>I usually keep my context in chats below 256k anyways so this would be tremendous honestly.
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This was posted 38 minutes ago, and as of 20 minutes ago, several Anthropic services are now designated as having a "major outage".<p>Doubt these are related, but it made me laugh a little.
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omg! new model!!
A bit of topic. But how likely is it that the US will restrict Chinese open weight models and also force Euro countries to do the same? I think it will be effective within 6 months. The US is having a hard time staying competitive.
I don’t know, but I do think that the days of the US “forcing” Euro countries to do anything, is over.
No it's not. The US dictates every single step in Europe. Euro politicians are in the pockets of American institutions. The biggest reason of dumb decisions in the EU is because of deliberate decisions made in favour of the US. LNG, war in Ukraine, ASML export restrictions and many more.
It isn't legally possible for them to do this at the EU level. The EU parliament would never vote for it.<p>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.<p>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.
Trump burned a lot of bridges in the EU, that one will be a hard sell
Why are Anthropic and OpenAI even allowing their coding harness apps to be plugged into different model providers…? I’m surprised they haven’t figured out a way to clamp down on that by now.
I'd guess because it costs them nothing and it gives you a smoother transition back towards paying for their products.
From my view, as soon as they do that, they send people out the door to use Opencode instead - and once many people have a taste of trying every model via Openrouter, it's eye opening as to the possibilities.<p>Of course - Anthropic and OpenAI have an advantage in the amount they can subsidize the usage, but I think those days are waning.
Well when a huge part of potential revenue is all in on Bedrock... you need the harness to be able to talk to Bedrock. And Vertex. And all the other places these models are hosted. And allow for proxy because many businesses do not all direct internet access... all valid business reasons.
It honestly should be easier, its a by product of everyone using the same API standard.<p>Codex and Claude require editing a .json file, but most other harnesses have direct connections via a /provider or /login command.