GTX 1080s: Testing a Legend | Hacker News Reader

GTX 1080s: Testing a Legend

lttlabs.com

112 pointsLabsLucas53 comments

I'm still using a 1080ti in my main PC, though I don't play as many games as I used to. Control is the last title I picked up where I really felt like I was pushing the graphics capability of my rig.

I remember when I built my PC I was surprised when I'd come across a post of someone running ancient (at the time) chips like the i7-870, and now I'm realizing I am one of those people.

My 2700X and 1080ti do plenty of what I need these days. I meant to upgrade both a couple years ago but between job changes and then tariffs and whatnot it just never quite made sense to commit to the jump. I have a hard time imagining what an ideal upgrade would even be now with how expensive everything's gotten. I'm mostly hoping my machine continues to hold up for another couple years.

I use it in my guest PC, it comfortably hits 165 fps in Rocket League at 1080p. Something about using the 1080 for 1080p feels poetic.

I still run a 2014 Mac mini and a 2012 MacBook air

My 2011 Mac mini nods sagely. It runs even better today than when it was new because I put an SSD in it a few years ago.

This is the first time Ive ever been concerned that my next PC will be a step down from my current due to costs.

It's amazing how great the 10 series was. The 1060, a budget card, had the same amount of VRAM as the previous generations top tier card (6GB) with the 1080Ti having 11GB! the 5060 for example has only 8GB, the same as the GTX 1070 and 1080.

The RAM crunch has been a quiet victory for those older cards. I have a 10 year old video card in my rig that had at the time a decent but not chart topping 8GB of RAM. Developers are still targeting 8GB because so many of the cards released today still have that. Since I'm still using 1080p the performance is usually acceptable too. Surprisingly the biggest problem is becoming the CPU, with the i5-3570k lacking a few of the later SSE instructions and being completely unable to run some titles.

SSE or AVX?

The cutoff is AVX2 instructions. They were introduced one generation later.

To be fair, the 5060 with 16GB is not that much more expensive than the 5060 8GB.

My old 1080 Ti now sits inside a 4U rackmount server. It's an EVGA SC2 HYBRID version and I am still amazed that the AIO cooler hasn't failed yet or leaked everywhere. One of the best things I've purchased in retrospect since it was my main GPU up until the middle of 2025, even though at the time in 2017 I felt the price of 1.5k NZD was extreme.

I have a similar plan for my 4090 once it's gaming days are over. I'll retire it into my homelab (I specifically massively overspecced the power supply in anticipation of this) and run whatever local AI models exist in 2028-2029 which can fit on it.

Funny enough, I have the 1080 and I tested qwen 3.5 9b on it today. I was positively surprised with the experience. It's no Opus but it did OK on the couple of queries and tasks I gave it. It's pretty impressive for a 10 year old gpu!

If it had more vram it could really cook. Qwen3.6-35b-a3b quantized to 3bits is genuinely usable for coding running on the ten year old pascal card with 16gb i picked up recently.

Mine is still going strong, it can run Gemma 4 26b. It can still play all the games I care about at near max settings at 1440p at 60 FPS (like Elden Ring).#

My PC did coincidentally die today (not GPU related) so I think it's time for an upgrade, what do you recommend?

Ryzen 5000 cpus are extremely cheap right now. I bought a 5900xt (16 cores) to upgrade a server a few weeks ago for ~$250. If you already have DDR4 you could put together a system for pretty cheap if you need it soon.

The downside is that AM4 is basically EOL, so no upgrade path.

> so I think it's time for an upgrade, what do you recommend?

Without knowing what you'll use it for, probably a 9970x + RTX Pro 6000 would do the trick, YMMV.

I don't know about you, but most of us don't want to drop $10k+ on a GPU!

Well, no one knows about anyone because no one is sharing what they want to use the hardware for! Kind of hard to give recommendations then :)

My 1080ti is my local inference machine now. With the release of the Bonsai 27B models I can run a genuine dense model with usable context. GOAT card.

What exact runtime are you running Bonsai 27B with right now and what variants of the weights are you using?

I have a 1080ti currently not plugged in. More info please.

Plug it in, get the cuda drivers, run ollama or equivalent, and go from there. I use an 4GB Quadro card from the same generation and depending on the model can get faster than I can read output. It’s not as good as commercial models, but smaller Qwens and Gemmas work well. The Quadro came with a Dell refurb that cost about as much as the card would have by itself at the time.

(I’m doing this with passthrough on a FreeBSD host with bhyve to a Linux guest. Works great.)

I’d like a beefier card, but until prices come down, even older cards like this can do some interesting things if you give them enough time.

Those were great and 1070 was a great deal. Upgraded to a 3080 from 1070 last year, they are quite reasonably priced now.

I have 3 3090s, all in various gaming computers. I’m not sure what to do with them- the VRAM is only 24GB so doesn’t seem worth the power costs to run an open weight model. Any suggestions on how I can run them as some type of cluster? Is it worth exploring NVLink?

One RTX 3090 would allow you to run either Qwen 3.6 model with ~100k context at Q4_K_M quantization. Two would definitely allow full context and then some, or go for Q8 quantization. You can do quote a lot of LLM stuff with one or more 3090s. Or give them to me and I will happily put them to use!

You can layer models across multiple GPUs for inference. If you pooled it into one system, that would be 72gb of some pretty damn fast memory. Would be great for dense models in the 30-50b range.

As others said, you can run more than one at a time, but even singly, 24 GB can be very useful in a hybrid approach. For instance, I recently had to process hundreds of high-res blueprints. Used Fable for the main orchestration, but all of the OCR and other work I did with a small local model. Didn't waste expensive Fable tokens on simple grunt work.

What are you using for OCR locally? This is something I've been considering trying for some time with old journals.

You can put dual 3090's into one system.

https://www.reddit.com/r/LocalLLaMA/comments/1m5fkts/my_prac...

Club 3090 will make installing llm easier, for 1 or more cards.

I bought two of these when they were new. I don't recall the price, but after mining some bitcoin in my electricty included apartment for a few months over the winter instead of running the heat, I think I ended up with ~.5 BTC.

1080ti is a remarkably great card that landed at just the right time - by far my longest used card before I needed an upgrade

    the legendary Core i7-8700K

This might be a unique assessment. My perspective is that Intel's strong lines were 4th gen and then 12th gen.

I see a number 4770 and 4790 still doing the job they were bought for. I expect the same for 12th gen when they're 13yo. Not so for anything between 4th and 12th.

> I see a number 4770 and 4790 still doing the job they were bought for. I expect the same for 12th gen when they're 13yo. Not so for anything between 4th and 12th.

What do you mean? My Core i7-6700K is still running strong on its Asus Z-170A mobo (TFA mention a Z370-A, mine's a bit older but was one of the first mobo to offer a M.2 NVMe slot). It even runs very modern games just fine on whatever not-so-powerful GPU that's in it: it's the PC my daughter uses to play (I did put PoP OS! and Steam on it but I'll swap to another distro if needed).

I switched to an AMD 3700X and then to an AMD7700X but I don't see anything wrong with my 6th gen Core i7.

I have i5-8600k OC to 5GHz and it's still decent.

I still have one too in a home server to power a local AI model. That being said, even my 3090 is starting to show its age. Recent games require aggressive DLSS (performance or super performance) to maintain at usable 70-80fps at 4K. That being said, in practice the upscaling isn't very noticeable.

I wonder if we’ll see deflationary performance pressure over the next year or two as hardware prices remain out of reach for most. If cards and VRAM aren’t available, will studios adjust and optimize for more meager hardware requirements instead of targeting what many users will have 18 months from now?

They still have great value in the used market. Swapped mine for a 3090, also used, for ~20% rebate.

I had a 1080 in my previous build, it was an OC model that went from 180 up to 250W and could perform about halfway between a stock 1080 and a 1080ti. That was a nice card but by late Covid it was really showing its age.

I just threw together my old 1060 in a steamOS - adjacent box running cachyOS. It’s great for couch co-op platformers. The GPUs were overkill for most games then and can still run new indie 2d games now.

1080 is a great card but the 1060 is an absolute king for its price back in the day, owned one and used it for quite a long time really. golden era of gaming and nvida

It's an older card running on high/ultra quality settings in those benchmarks. I would be more interested in low/medium settings.

1080 here with 7950X3D+96GB.

Haha that’s amazing. I thought these things were practically worthless. Gave mine away for free on Reddit.

I wish NVIDIA made rastering-only card. No RT, no AI cores, just pure performance

Crazy for me to still own two

I own four in my office. Daily driven, mostly with photo editing tasks but some Blender, too. Work well for us.

i still have a gtx 1080 in my machine. But nvidia just dropped support for them, and some games will forever remain glitching (ex 007 first light flickers like crazy on proton)

What's legendary about the 1080? It's a smaller 980ti on a much smaller node.

Less energy usage, more vram, faster in games (see https://www.pc-kombo.com/us/benchmark/games/gpu/compare?ids%...).

But it is even more about timing. Nvidia shifted to RTX afterwards, opting to go for raytracing and upscaling instead of making strictly faster cards. Which made the last GTX cards very competitive for regular usage, raising its status.

Something I can't fault nvidia for is long term vision. If you ignore all the non-gaming uses, I can't see significant gains to be had by keeping evolving rasterization based rendering, which presumably would hit diminishing returns, upgrades would be less exciting, and be easier for AMD and others to compete against them. The trouble is a variety of reasons has meant that long term is likely going to be over a decade from when it was introduced before it's really commonplace or part of the furniture for the majority of games.

It's the same architecture of the 980 on a smaller node, that's it.

It's not considered a legendary card by the industry.

Still rocking GTX 1080. I barely need an upgrade as I avoid UE5 slop.

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