IBM CEO says open weight models are now good and cheap on-prem
161 points - today at 1:47 AM
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I do use Anthropic and OpenAI mostly because it costs me 1/40 and 1/50 of the api prices, which is way cheaper than Chinese subscriptions, but Iām ready to jump ship when they pull the plug. Fortunately they have nothing that forces me to keep paying them, and I donāt pay the crazy enterprise subscription costs, just the personal account prices.
I also die to be able to run the OSS setup locally to stop being spied on all the time.
For context, I averaged 10 hours a day prompting LLMs from when ChatGPT came out. At the start it was just function generation, then single file modules, then modules, and now I reason, design, implement and test with them.
An interesting thing is that with omp you can plan with a smart model and then implement with a dumber one. So for example, plan with Kimi 3.1 via OpenRouter and then implement with DSFV4 with zero data retention active, sorted by cheapest, and minimal tps accepted.
I get the people who are pissed about their cushy jobs evaporating, but if you know how to use these technologies itās very freeing because itās like having a company of people working for you, except they are not human so theyāre not wasting their life working for you instead of using it for themselves.
You can make them do pretty much everything that is fuzzy-verifiable, you donāt have to worry about their feelings or that they wonāt do what you asked them to do or stop, and you can activate them when you want at scale in parallel or not use them at all for days.
For me itās a dream honestly. I never felt so much empowered in my life while being enabled to unlock my creativity with almost no boundaries.
This is a win though. But not for the reasons people might think it is.
It is a win because it's a massive player now countering the new (temporary) behemoths. With all the leverage, budget and connections.
And contrary to the AI Labs, IBM isn't just that one SV rockstar dude, but a whole org with tons of people. Meaning that they're going to be far closer to the baseline of sane humans just from averaging alone.
While he thinks most businesses can build useful AI infrastructure in just two or three racks, he feels many will struggle to get it running.
āThe question becomes: how do you do that?ā he said. āThe question that the enterprise struggles with is: āWhere are my kernel engineers? Where are the people who worry about the underlying network? Who can make sure that the model is clustered on GPUs that are close to each other in network proximity? Who can make sure that youāre doing the right caching of results so you get an incredible response?āā
Has he heard of āagentic AIā? You simply fire up Claude or ChatGPT and ask it how to do all of the above.