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- Hacker News
- This is historic. For the first time, an open-weights LLM is right at the top.
We won't be able to run this ourselves, but many providers can.
by davidkunz - > For the first time, an open-weights LLM is right at the top.
Hmm, not quite true, I think that honor, for better or worse, goes to OpenAI. When they released GPT2 (or GPT1 for that matter) is was quite literally the SOTA in the ecosystem when it was released.
- Given the frontier-level capabilities of Kimi K3, I'm wondering if it's possible to extract the core capabilities (fundamental reasoning and tool calling) of the model into a smaller one that consumer devices could run? Not sure exactly how, but either by heavy distillation or some other surgical method since Kimi has a Mixture of Experts architecture.
I think it's very valuable to have a smaller model that doesn't have any domain knowledge or facts built into its weights, but given the right context, could accurately reason about what to do and use the right tools.
I'm aware of colibri [1], but so far I've only seen extremely slow performance.
- > smaller model that doesn't have any domain knowledge or facts built into its weights
I’m not sure it works this way. Language modelling itself is a “domain”, and if it didn’t have a grasp language it wouldn’t be able to do anything else.
I also think a “reasoning engine” that had to reason through everything from first principals would likely be extremely inefficient.
It’s good went models have domain knowledge and expertise - and all of their reasoning flows downstream of that
by wolttam - Why not generate an artificial dataset using commercial APIs and then finetune a small model on this data?
I’ve had success adapting even a 7B model for single-domain tasks that way, including reasoning and tool calling.
You can use an open model. The point is just to outsource the inference, so you don’t have to deal with running the larger model yourself.
by leobg - There’s another way besides distillation that’s way cheaper: You can have the big model build prescriptive skills that the small model follows.
Take the “train” portion of tasks on some benchmark, have K3 complete it, and then output detailed descriptions of tools used and why, then run the validation tasks with some small model that has access to the skills.
by clbrmbr - "I'd like a car that goes 300mph and gets 100mpg while doing it. I'm aware of a car that gets 100mpg but it is extremely slow."
You are describing fundamental tradeoffs. Getting more performance relative to model size and training token amount is what all of the labs are solving.
by snemvalts - Getting 404 on the OP's link. Does it mean it got banned or self-censored in the meantime?by storus
- At the risk of sounding like a conspiracy theorist, this sounds like a great opportunity to make a statement. US or China, but likelier to be the former. Maybe Clem's on a call with the US government right now?by achrono
- It's up nowby craigmart
- I imagine it's just technical issues on the flip. It's also going to be interesting what happens to HF with loads of people downloading a many TB model. Even though almost no one has the capability to run it, it does seem like something to stash away in case it suddenly becomes unavailable due to government controls.
FWIW, China is suddenly talking about model export controls. It was one thing to release also-ran models, but now that they're pushing SOTA it's a different game.
by llm_nerd - Until a few minutes ago there was a countdown page. (The weights haven't been released yet.) The countdown should be over in 19min, not sure why we're suddenly getting a 404.by codethief
- After going through the license and trying out the model on some hardware, I don't think it will ever will be 60-70% cheaper than the price Moonshot is offering from providers, it be marginally lower sure but discounts we saw with GLM seem hard unless tps is put into the ground.
In my testing it seems like Kimi has a healthy margin (I would wager 40-50% if they are renting GPUs at full marked up prices, a bunch more otherwise, given their tps, but I don't know which GPUs they are on and what they consider margins and if they own them) but definitely not the claimed 90%+ margins of Anthropic (honestly I am suspicious of even 80% API margins for Anthropic) as I have seen some people posit. If it was just electricity costs I could bet it could be 80-90% though otherwise it seems rough given the TPS they offer.
I would love if someone has access to those super secret R100s could try it, and tell us if it's significantly cheaper since I think immediate memory optimizations seem hard since I am already on a quantised model. And not even using 1M context.
All I had access to was B200(couldn't find a B300). I am certain people could optimize it a lot better but Kimi also wants some kind of contract for big providers so I think we shouldn't imagine any significant discounts while Kimi is the top open model around.
by minraws - In my opinion, next step is to cut down on reasoning tokens while maintaining intelligence. The Chain of Thought and looping can still be an issue with these Chinese models. They in fact said K3 would improve in the area but it's still an issue that unfortunately harms the token cost wins a bit. OpenAI has been really impressive here, on the opposite end of this.by jug
- Yeah, they thing forever and doubt everything "wait but" for 200k tokens for almost any question.by XCSme
- There is a really interesting startup in Prague that is doing just that. They fine-tuned Qwen 3.6 27b to have 46% fewer reasoning tokens while maintaining most of the performance characteristics. I'm interested to see if they continue down this path of optimizing reasoning for other models.by kamranjon
- I suggest downloading these frontier models just to have a copy; even though it’s 1.5TB, it’s worth sticking in a cheap disk and putting aside. Seeding torrents would be even more useful. The man is coming to lock these down, like they tried to do with encryption algorithms. The only way open software survives regulation is through distribution.
Over time the enormous investment in techniques and hardware manufacturing will almost certainly make these runnable in a more practical way. It will be a shame if by the time we get there it’s illegal to distribute them and you have to pay a reg capture premium and feed the machine.
by fnordpiglet - There's no such thing as cheap disk anymore and I'm not spending hundreds of dollars out of paranoia of "the man".by mvdtnz
- they will just restrict you from buying the hardware these run on
- Here: https://terminalbytes.com/kimi-k3-torrent/Kimi-K3.torrent
Magnet:
magnet:?xt=urn:btih:1e63a865fbf9b58decc8b71091db54d673c5da6f&dn=Kimi-K3&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A6969%2Fannounce&tr=udp%3A%2F%2Fopen.stealth.si%3A80%2Fannounce&tr=udp%3A%2F%2Fexplodie.org%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.torrent.eu.org%3A451%2Fannounce&tr=udp%3A%2F%2Fexodus.desync.com%3A6969%2Fannounce
by hemant6488 - It is online on https://app.fireworks.ai/models/fireworks/kimi-k3 (Uncached Input $3.00/M Cached Input $0.30/M Output $15.00/M)by MeProtozoan
- Yep, it’s also availability on Together.ai for your sale price. Fireworks and Together were the first places I checked!by dkersten
- I love fireworks.ai! They launched it couple of hours ago and we have it now already live on our platform for our users. Just a shame they deprecated the on-demand flux models :( Where do I get my fix for image gen now?by lmf4lol
- Comparing to Opus 5: Claude Opus 5 (Uncached Input $5/M Cached Input $0.50/M Output $25/M) but you also pay a premium on Cache write 25% for 5m and 100% for 1h.by tidbeck
- Fireworks' priority tier of Kimi (at $3.75/M vs. Moonshot's $3.00/M) is available on OpenRouter as well. https://openrouter.ai/moonshotai/kimi-k3#providers
Currently it's showing significantly better latency, but at a fraction of the usage Moonshot is experiencing, so we'll see how that holds up - regardless, a same-day deployment is an impressive feat!
by btown - from the license:
If the Licensee or any of its affiliates operates a Model as a Service business, and the aggregate revenue of the Licensee and its affiliates exceeds 20 million US dollars (or the equivalent in other currencies) in total over any consecutive 12 months, the Licensee must enter into a separate agreement with Moonshot AI before using the Software or its derivative works for any commercial purpose.
by dilliwal - If you put a layer between the customer and the LLM, a la ChatGPT/Claude, are you a Model-as-a-Service business? I think you are not.
But then how thick does that layer need to be?
I think the real win from these models is enabling well-funded/profitable companies to not be beholden to the big closed-weight providers. But I like the idea of letting a hundred flowers bloom for under $20M/y each.
by biztos - good find! This sounds a bit like what Meta was doing with the earlier Llama models?
There is also this paragraph in their licence that is smart marketing-wise:
> 3. If the Software (or any derivative works thereof) is used for any of the Licensee's commercial products or services that have more than 100 million monthly active users, or more than 20 million US dollars (or equivalent in other currencies) in monthly revenue, "Kimi K3" must be prominently displayed on the user interface of such product or service.
by gorgmah - Many people are talking about price, but I think that the most interesting aspect of this release, by far, is customization.
Any startup can download the weights, tinker with them, and fine-tune them. The real win here isn't necessarily cost, but performance on your data and IP sovereignty. It's a huge win. Kudos to the Kimi team.
by rushingcreek - Who does this, though? I'm truly curious.by otterley