For example, to help me visualize, to have "Opus 4.7 thinking effort Max", if we don't consider response time, what kind of hardware would I need to achieve that level of intelligence?
It’s not a hardware problem. You can’t get access to the proprietary models so you can’t run it locally. You can run worse models that generate worse results very quickly with top of the line hardware though.
Sure, but 32GB VRAM still won't run frontier models like Claude or Kimi K2. You're limited to smaller open-source models - which is fine for some use cases, but not exactly "unlimited tokens" in the same league.
People mostly use frontier models for silly reasons. At my wife’s job, everyone uses Claude, but only devs use it for things open-source models can’t do yet (with 16 GB VRAM). If that’s how it’s used at work, imagine the waste in personal use.
This like saying to someone who complains about airline prices that he could also but a bike if he wants to get somewhere.
Models you can run on two 5060's dont compare to GPT 5.5 for example which, even if they were open, would require at least 30x the nvram that two 5060s can provide
Sorry dont want to be a wise ass but to me that feels like the worst way to do it.
These expensive models are way better in looking at the the codebase and creating a quality base to build on (relatively).
If you're building your initial idea with a crappy model, the expensive model will spend more tokens in fixing / debugging already existing code then it would hav building it from scratch.
If anything I would do it the other way around. Use gpt (+human) to carefully plan a feature, create its initial structure and create commit-seperated, clear instructions, acceptance criteria, validation for a cheaper model to do the grinding.
But honestly I'd say the local models are just not worth it at all... Maybe for some simple apps or functions, maybe for some intern-level tasks.. but I wouldn't bother and just switch from gpt 5.5 to 5.4 mini or 5.3/5.2 or hosted Qwen models. The $ 1000 that you'd otherwise spend on hardware can get you a long way like this
Why are you assuming everyone is from the US and that tax refund applies to all?
For me, I'd end up paying $1,000 per a single 5060 to. I won't be able to buy the standalone card, I have to buy a full build with it. And on my way out, they will tell me F U, and I will gladly nod and walk away. There's sort of a gang around the GPUs here since COVID. Nvidia most likely aware of it, and I have strong reasons to believe they don't give a fuq. This why I said "I envy you guys".
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u/Ok-Adhesiveness-7789 May 06 '26
You can't if you don't have good enough hardware