Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

emergingtrajectories.com

Post reply on HN
Print view View original

31–40 of 349 posts

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#31

Post by mwryl »

bko wrote: post #5

I think the risk is overstated. For one, on the margin people are willing to pay a lot for slightly better models. I know personally the value the LLM adds to my workflow is considerably more than the $200/m I pay the frontier labs. I have no interest in optimizing that to get it slightly lower. There are a very vocal minority that optimizes this or companies whose LLM expense is marginal, but I think that's the mino…

I don't think subs are what keep their lights on. And their API is so absurdly expensive. For the harness hard disagree but ultimately its up to each ones taste. You may want to check this tho https://harnessrank.net

On our side we use Claude/GPT/Kimi (it replaced Antigravity) for development. But we build our systems around a cheaper denominator (Deepseek previously, recently we added GPT 5.6 which have good prices as well). We offer BYOK for Claude but its def not an option to build something on top of it (for us).

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#32

Post by torginus »

Upper bound of AI progress - recursive self improvement. In this case AI will be responsible for building better models, making people who own datacenters the winners. Anthropic/OAI is cooked.

Lower bound of AI progress - plateau. Progess is slowing, focus is on serving a meaningful peak capability at the lowest possible price. There's been news today that Google is building a Gemini chip with weights baked into silicon. Considering a chip's lifetime of 2-3 years at minimum, and that a 2-3 year model today would be useless today, they're expecting they wont make a similar amount of progress in the next 3. Game is about selling at the lowest margin. Anthropic/OAI is cooked.

So their survival rests on the presumption that AI progress will fall between these two extremes.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#33

Post by sim04ful »

bko wrote: post #5

I think the risk is overstated. For one, on the margin people are willing to pay a lot for slightly better models. I know personally the value the LLM adds to my workflow is considerably more than the $200/m I pay the frontier labs. I have no interest in optimizing that to get it slightly lower. There are a very vocal minority that optimizes this or companies whose LLM expense is marginal, but I think that's the mino…

I'm not sure about the harness now: https://github.com/lidge-jun/opencodex

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#34

Post by __bjoernd »

simianwords wrote: post #22

To everyone praising Open weight models, could you answer a simple question? If Anthropic doesn't make money because of distillation attacks, how would they convince investors to invest in them, such that it makes financial sense for Anthropic to train even bigger models? Assuming it is preferable for everyone that we get better models in the future. Distillation attacks remove the financial incentive.

This assumes all the open models are just a result of distilling Anthropic models. Which remains to be proven.

And if they are, the point remains that Anthropic has a brittle product advantage that users and investors should be cautious about.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#35

Post by in_a_society »

torginus wrote: post #32

Upper bound of AI progress - recursive self improvement. In this case AI will be responsible for building better models, making people who own datacenters the winners. Anthropic/OAI is cooked. Lower bound of AI progress - plateau. Progess is slowing, focus is on serving a meaningful peak capability at the lowest possible price. There's been news today that Google is building a Gemini chip with weights baked into sili…

Baking weights in makes a lot of sense for inference speed and power efficiency and has the added benefit of putting many end-users on the hardware refresh treadmill.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#36

Post by Alpha3031 »

simianwords wrote: post #22

To everyone praising Open weight models, could you answer a simple question? If Anthropic doesn't make money because of distillation attacks, how would they convince investors to invest in them, such that it makes financial sense for Anthropic to train even bigger models? Assuming it is preferable for everyone that we get better models in the future. Distillation attacks remove the financial incentive.

I don't think the timeline is plausible for Moonshot to have done any distillation from Fable, which means any distillation training data would have been from Opus.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#37

Post by drakythe »

overgard wrote: post #14

I keep thinking about the Figma thing. If you're unaware, here's the google summary: ---- The Board Departure: Mike Krieger, Anthropic’s CPO and a co-founder of Instagram, sat on Figma’s board of directors. He resigned on April 14, just days before news of Claude Design broke. This sparked speculation over conflict of interest and the use of proprietary product strategy information. Betrayal of Partnership: The launc…

Our current incarnation of capitalism is all about monopolistic behaviors. If these LLM companies do get to the point of being able to replace employees I fully expect them to stop selling shovels and start producing the gold directly, anyone else be damned. And, frankly, this has always been the case. If a product is built on top of another service it has a limited lifespan. Either the product will be purchased or it will be replaced by the service it depends on. How many "killer apps" has Apple silently absorbed into iOS over the years?

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#38

Post by monster_truck »

overgard wrote: post #14

I keep thinking about the Figma thing. If you're unaware, here's the google summary: ---- The Board Departure: Mike Krieger, Anthropic’s CPO and a co-founder of Instagram, sat on Figma’s board of directors. He resigned on April 14, just days before news of Claude Design broke. This sparked speculation over conflict of interest and the use of proprietary product strategy information. Betrayal of Partnership: The launc…

You are vastly underestimating how much more profitable a 10% annual return on GPUs is than basically anything else you would use an LLM for.

They think whatever you are doing is cute and would very much like to ensure their models can do it even better in the future, but competing? Not even worth the time to think about

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#39

Post by philipkglass »

In November of 2025, I would have said that Anthropic's Opus 4.5 model together with their Claude Code harness was the first and only system where a well-specified software feature could be implemented correctly for me in one shot. Today, I'm about equally happy to use Claude or Codex. And if both of those start to squeeze customers for money or get too zealous about safety it looks like there are going to be plenty of capable open weight models and true open source harnesses to use with them. Even Google might eventually deliver a capable model + agent combination (Gemini 3.1 Pro still seems pretty strong, but Antigravity was inept the last time I tried to use it.)

I'm happy if Anthropic's business remains viable as one of several strong competitors. The company's safety-first ethos is driving them to increase refusals and deliberately-built-in ignorance with their newer models. In the long run, Anthropic may be best remembered for accelerating the development of software in general so that other people could build less timid tools.

Re: Kimi K3, Qwen 3.8, and Anthropic's (Potential) Unravelling

#40

Post by arrowleaf »

bko wrote: post #5

I think the risk is overstated. For one, on the margin people are willing to pay a lot for slightly better models. I know personally the value the LLM adds to my workflow is considerably more than the $200/m I pay the frontier labs. I have no interest in optimizing that to get it slightly lower. There are a very vocal minority that optimizes this or companies whose LLM expense is marginal, but I think that's the mino…

Here, people tend to forget about enterprise customers. Enterprise is excluded from using these heavily subsidized subscriptions, I know of orgs that are spending around $500k/month for teams of ~100 developers actively using AI.
Post reply on HN