I think there’s a reasonable argument that a burst bubble will cause prices to drop. Prices are very high because they’re trying to justify these trillion dollar valuations on IP alone. If that fantasy goes away then prices will fall down to just silicon and electricity, which looks more like Chinese model prices. Hard to say how it will play out but the direction isn’t obvious to me.
Yes, today is not a great time to purchase hardware.
When I bought, I paid $850 a piece. And I needed one anyways for the gaming I was going to do.
My guess is the next good time to buy is going to be 24-36 months from now, depending on how the AI bubble goes.
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I'll add to this, I personally don't like Apple hardware (not so much related to the hardware as their company philosophy) but their machines with unified memory (or AMDs latest unified memory offerings) get pretty equivalent speeds to my 3090s, and are probably a much better modern entrypoint to local llms.
There's a reason the joke is that Silicon Valley software devs bought up all the Mac minis for OpenClaw.
You can get a 48gb unified RAM M4 pro mac mini for ~2k. If you're not going to do much else with the machine, it's what I'd pick as my budget inference device right now. Spend a year of claude now, get ~150tok/s for the next decade (plus) for ~free.
If you want more capable and are willing to spend a little more, go with the newer Ryzen AI Max+ 395 machines.
You'll spend less on power too.
My last suggestion would be to go buy an RTX3090 at this point. You can do a lot better for a lot cheaper.
I run qwen 27B:Q4 @ 130k context at 50 t/s on a single R9700, and have a 7900XT that runs mellum 12B:Q8 as its subagent. R9700s do really well at low wattage and underclocking as well. It's designed to run at 300W, mine is throttled at 210W, and only had an 8% slowdown. If I had somewhere else to put my desktop in my house, I'd bump it up to 240W and there would be zero perf degradation.
1x RTX3090 is absolutely not overkill for gaming however. Nowadays it's barely enough to get 60FPS in 4K in some recently released games. But the shocking part is that my 3090 is still probably worth as much as when I bought it about 4 years ago.
I can’t run 4k HDR cyberpunk 2077 at 240hz with path tracing. I’m managing ~120fps. I’ve got a Blackwell 6000. I didn’t buy it for games, but there are still games and setups where the GPU is the bottleneck. I don’t even have an 8k TV.
There is currently no gpu in production that can max out the largest and fastest displays in graphically demanding games. We have monitors that are the equivalent of two 4k monitors side by side and run at 240hz. I have a 5080 and have to turn down settings to get 60fps in cyberpunk.
That's how most raytracing is done these days anyway. The game is rendered at a much lower resolution, the raytracing math is applied, and then it is upsampled to the target resolution.
If you set the target resolution to 1080p, not much changes in the render pipeline except the that final upscaling step. To get better quality, the lower resolution is bumped up so there is more data to work with for the upsampling, but the scaling performance can be very hit or miss depending on the game as the engine itself often can play a huge role in rendering performance.
As far as rendering the 1080p image at 4k, yea it works fine, but there will always be little artefacts that remain for those looking for them. 1440p seems to be the sweet spot for gamers today, but 4k is really nice for when you're not gaming as most online video is now made for dual use on televisions.
AFAIK nvidia cards dont work in tandem (aka sli in the past) very well these days. So that aint true.
Also, 2 gens old means bad performance at ray tracing, abysmal path tracing if at all. Pretty sure it can't run smoothly CP2077 in native 4k without dlss upscalers with all on ultra.
That's not my experience, and the trajectory is good anyway - what doesn't work perfectly today will be just fine in a few months.
In a quickly moving field, it's amazing how much money one can save by overcoming FOMO and not living on the bleeding edge. It's like waiting for Steam sales, the games will be just as good.
Curious what model you're using that works well on a 16GB card? I very much want to use my 5080 for inference, but everything I've tried so far has either just not been good enough or painfully slow.
I have a 5080 too! For me, the key has been dropping Ollama for Llama.cpp, which is not particularly scary to configure anymore and just skyrocketed performance. I download the models with LM Studio, then run them with llama.cpp.
That should do pretty well. Memory bandwidth is the biggest bottleneck for token generation, at 644 GB/s you should be able to do pretty well on a 9070, while prompt proessing is more compute bound and Nvidia tends to have the edge there.
16 GiB won't fit you much, so you'd probably want at least 2x, and preferably 3x of those, and then you need a motherboard, power, etc. that can handle that.
I cheaped out and got 2 7900XT I get about 80 tps on qwen3.6 35b a3b. The cost when I got them before the memory crunch was $1400ish. On retrospect I should have forked over a couple hundred more and gotten the 7900XTX for the extra VRAM.
You can get 60tps with three 1080tis and the sparse model, and I bet two 16gb 5060tis would do the same for ~1200. One 3090 is enough for a useful system, even on an old am4 host.
Dual 5060ti 16gb does over 100 tok/s on 35B A3B. Even with PCIE Gen 4 x4, which quite a lot of motherboards can do. Though Gen 4 x8 or Gen 5 x4 is slightly faster. Misc working notes on this hardware combo here, https://github.com/jonnor/embeddedml/tree/master/handson/mic...
In 3.6 years, chances are they are still worth $3k. Unless some new chip fab pops up that can spam the chip market. Even if the AI bubble bursts, I doubt we'll see high-RAM GPUs sell off.
