What happens to older datacenter GPUs? Do they have a second life somewhere outside of datacenters?

I could see Nvidia adding terms of sale requiring disposal rather than resale.

Plenty of enterprise server hardware (racks, servers, RAM, disks) does have an active secondhand market after 3-5 years of use, but I think GPUs are too specialized for it to be viable. I doubt anyone has the setup to run a H200 in their home rig.

I also don't think companies are going to have mandatory replacement cycles for GPU hardware the same way they do for everything else, because:

1. It is an order or magnitude (or more) more expensive.

2. It isn't clear whether Moore's law will apply to the AI GPU space the same way it has for everything else.

Unless Nvidia can launch a new chip every 2-3 years with massively improved performance-per-watt at a lower price no one is going to rush to recycle the old one.

Last I checked AWS is still offering g4dn instances that run on NVIDIA T4 GPUs, which were first released in 2018. I think most people underestimate how long superscalers can keep these things running profitably after they depreciate, and you probably don’t want anything they throw away.

My last employer is still running a bunch of otherwise discontinued g3 instances with 2015 era GPUs.

It's likely the GPU boards are designed for water cooled data center racks and might not fit in a regular PC case. It's also possible the PCB the GPU's are mounted to might not be standard PCIe cards that fit into an ATX case.

I bought a used NEC SX Aurora TSUBASA (PCIe x16 board that looks like a GPU board) and realized it has no fans. The server case it is designed to fit into is pressurized by fans forcing air through eight cards on a special 4 + 4 slot motherboard. I have to stack and mount three 40mm fans on the back.

They are build to physically last 5-7 years in 24/7 datacenter use, but they have effective lifetime just 3-4 years, then their value has deprecated and electricity and infrastructure cost dominates. Meta did a benchmark where 9% of the chips failed every year, 'infant mortality' is much higher in the first 3 months of use.

Depending on the elemental composition, it could definitely be worthwhile to recycle wherever scale is practical. For giant datacenters and companies using hundreds of thousands or millions of gpus, that adds up to a lot of gold and other valuable elements.

In order to take advantage of that, someone needs to be positioned to process all that material economically, and to make the logistics achievable by the big players. If it costs Facebook $10million to store and transport phased out gpus vs just sending them to a landfil, they're not going to do it. If they get $100k for recycling - probably not going to do it. If they pocket $5 million, they will definitely contract that out, especially if it costs $50 million to build out the infrastructure to handle it.

Probably a good company idea - transport, disposal, refurbishment of out of cycle GPUs and datacenter assets, creating a massive recycling pipeline for recapturing all the valuable elements is a pretty good niche.

I've written about this elsewhere but I predict there will be a significant secondary market for repurposing parts of datacenter GPUs (for example, RAM chips) by desoldering them and soldering them onto new PCBs that fit PC/consumer use cases.

No affiliation (I wish), but: https://gptshop.ai

This site apparently sources ex-enterprise(-only) systems and puts them into desktop style enclosures.

It seems like GPUs with a high utilization rate (60%+) degrade after 1-3 years: https://www.tomshardware.com/pc-components/gpus/datacenter-g...

Would be interested to know if others have takes on this.

You send them back to Nvidia or a third party e-waste recycler at end of life. Sometimes they're resold and reused, but my understanding is that most are eventually processed for materials.

Bin!!

Why would them sell it cheaper to the 2nd market??

It will hurt the sales of new ones. This is the way even with food, let alone technology. Don't expect to buy cheaper 2nd GPU any century soon.

This article misses the point that people are still actively running older compute.