51–60 of 199 posts
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This comment would be much better without the second line
I know it's a hard ask on this site, but I need you to start parsing content and not tone. It was a helpful bit of context, even if it was a bit vitriolic.
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Open source projects frequently have separate commercial licenses no? This isn't abnormal.
No, I don't know a single project I'd call "open source" (as understood by the FOSS community) that restricts what you can do with it, that'd make it very much "not open source" as you're discriminating against specific persons/groups/fields of endeavor.
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Open source AI is actually a lot less "powerful" than genuine frontier models, i.e. it has a much tighter inherent capability ceiling. This is "decelerationist" from a purely AGI-pilled point of view but it's actually great if you're worried about a capabilities arms race putting AI Safety at severe risk. Kimi K3 is plausibly a lot less dangerous than a totally jailbroken ChatGPT/Gemini/Claude Sonnet (let alone Opus…
Do you think they are inherently less powerful? I'd imagined that closed labs have a head start / more funding so the open labs are playing catch-up. Is there a world where open source models end up at the frontier, or do you think there are structural/first-principles reasons why this won't happen?
What would it take to get an American open model to compete with this?
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No, I don't know a single project I'd call "open source" (as understood by the FOSS community) that restricts what you can do with it, that'd make it very much "not open source" as you're discriminating against specific persons/groups/fields of endeavor.
GPL licenses also restrict what you can do with it...
License: https://huggingface.co/moonshotai/Kimi-K3/blob/main/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…
I wonder how they'll figure out who to target for litigation when this license is violated.
It is a very rare (and ballsy, and perhaps incompetent) company that ignores their lawyers' recommendations to adhere to the letter of all of the software licenses they are bound to.
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I know it's a hard ask on this site, but I need you to start parsing content and not tone. It was a helpful bit of context, even if it was a bit vitriolic.
Why should I waste time parsing content and not tone? Why can't the commenter just avoid the tone? It even saves time since you can write less!
If you are a large enough company that spends million+ on inference a month, it makes sense to buy a GB300 rack ($6M on top range from what I could find) which has 20.7 TB. Since the model is mixed trained (MXFP4), you would need less than 10% of the rack's memory to serve the full model. Aggregate HBM bandwidth: 576 TB/s. You can run over 6000 parallel agentic workflows (each with ~100k context on average) at ~30 tok/s.
Assuming the annual amortization+electricity at $1.5M/year and about 50% average annual utilization, you get less than 60 cents (USD) per million output token, for a frontier model with plenty of capacity to share, all your data never leaving premises and well over an order of magnitude cheaper!
As long as a company believes that the openweight models will continue to get more capable and 'AI is here to stay', this model provides the first solid footing for a decision to just buy a rack.