IBM CEO says open weight models are now good and cheap on-prem

It's absolutely true. I have three different setups here, a rig with 8 gpus that I use in either one of two modes (all 8, very heavy model or just one much lighter) and two DGX sparks. I haven't used a paid model in months. Sure, they use a few more tokens and the results may be slightly less good (but this doesn't really matter because I'm still in the loop so it is easy to correct). But the fact that I'm not sharing my work with the paid providers is much more to my liking than having big brother looking over my shoulder at every step and occasionally giving me the 'I can't let you do that, Jacques' treatment.

You can try open models via OpenRouter and omp without having to buy or rent any GPU. I routinely try open models to see where they are. GLM 5.3 with DSFV4.1 as advisor via omp feels Opus 4.6 level, i.e. totally able to ship stuff. 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 I’m ready to jump ship when they pull the plug. Fortunately they have nothing that forces me to keep paying them, and I don’t 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 it’s very freeing because it’s like having a company of people working for you, except they are not human so they’re 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 don’t have to worry about their feelings or that they won’t 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 it’s a dream honestly. I never felt so much empowered in my life while being enabled to unlock my creativity with almost no boundaries.

I think, despite the desperate attempt at IBM to remain relevant (and in business), their CEO has a point here that do you really need SOTA models for everything? I had a really nice time with GLM5.2 for a month or two - it was, in my experience, approx Opus 4.5ish level of capability when I think Opus 4.8 was the new hotness Even today, I use Gemini 3.8 Flash as my daily driver for most coding. Its fast and good, even if it is not the absolute SOTA at coding benchmarks it really is very good. Yes I have tried Opus 5.5 and 4 Argon etc and yes the are better, but do I need that? I think that we are going to be at the stage soon-enough where models are "good enough" for 99% of people's needs. The SOTA will keep on marching ever-onwards I am sure, but I would not be surprised if people stick with previous-gen/previous-previous-gen/etc models because why upgrade? If this does play out like this, I do wonder how that works out for the frontier labs (specifically OpenAI and Anthropic, less so Meta & Google) - if open models or even just cheaper Sonnet-level models from a few generations ago are good enough for basically everyone's daily work, where is the revenue? how can you justify pumping billions and billions into new generation models and datacenters etc when there is no driving need to use them?

How good will be the business of dealing with 2nd hand GPUs for open weights model in the future? What will the AI labs do with their GPUs once they are beyond their EOL? Can somebody please advise? I was able to get this related article https://rcrtech.com/semiconductor-news/what-happens-to-old-a...

But hardware to run them is conveniently something IBM would be happy to sell you.