As everybody is aware, the world is still going nuts attempting to develop more, more recent and better AI tools. Mainly by tossing unreasonable quantities of money at the problem. A number of those billions go towards developing low-cost or totally free services that operate at a considerable loss. The tech giants that run them all are wanting to attract as many users as possible, so that they can record the market, and end up being the dominant or just party that can offer them. It is the classic Silicon Valley playbook. Once supremacy is reached, anticipate the enshittification to begin.

A likely method to earn back all that cash for developing these LLMs will be by tweaking their outputs to the liking of whoever pays the most. An example of what that such tweaking looks like is the rejection of DeepSeek’s R1 to discuss what took place at Tiananmen Square in 1989. That one is certainly politically motivated, but ad-funded services will not exactly be fun either. In the future, I completely expect to be able to have a frank and honest conversation about the Tiananmen occasions with an American AI agent, however the only one I can afford will have presumed the personality of Father Christmas who, while holding a can of Coca-Cola, will intersperse the stating of the tragic events with a joyful “Ho ho ho … Didn’t you know? The vacations are coming!”

Or maybe that is too improbable. Today, dispite all that cash, the most popular service for code conclusion still has trouble dealing with a number of simple words, despite them existing in every dictionary. There should be a bug in the “complimentary speech”, or something.

But there is hope. One of the tricks of an approaching gamer to shake up the market, is to damage the incumbents by launching their model totally free, under a liberal license. This is what DeepSeek just finished with their DeepSeek-R1. Google did it earlier with the Gemma models, as did Meta with Llama. We can download these designs ourselves and run them on our own hardware. Better yet, people can take these designs and scrub the predispositions from them. And we can download those scrubbed models and run those on our own hardware. And after that we can lastly have some genuinely useful LLMs.

That hardware can be a hurdle, however. There are two alternatives to select from if you desire to run an LLM in your area. You can get a big, powerful video card from Nvidia, or you can buy an Apple. Either is costly. The main specification that suggests how well an LLM will carry out is the amount of memory available. VRAM in the case of GPU’s, typical RAM in the case of Apples. Bigger is much better here. More RAM suggests larger models, which will dramatically improve the quality of the output. Personally, I ’d state one needs at least over 24GB to be able to run anything beneficial. That will fit a 32 billion criterion model with a little headroom to spare. Building, or purchasing, a workstation that is geared up to manage that can quickly cost countless euros.

So what to do, if you do not have that amount of money to spare? You purchase second-hand! This is a feasible choice, however as always, there is no such thing as a totally free lunch. Memory may be the main concern, but do not underestimate the importance of memory bandwidth and other specs. Older equipment will have lower performance on those aspects. But let’s not worry too much about that now. I am interested in building something that at least can run the LLMs in a functional method. Sure, the most recent Nvidia card might do it faster, however the point is to be able to do it at all. Powerful online designs can be good, but one should at the minimum have the choice to switch to a local one, if the scenario requires it.

Below is my attempt to develop such a capable AI computer without spending excessive. I ended up with a workstation with 48GB of VRAM that cost me around 1700 euros. I might have done it for less. For circumstances, it was not strictly required to buy a brand new dummy GPU (see below), or I could have found someone that would 3D print the cooling fan shroud for me, instead of delivering a ready-made one from a distant nation. I’ll confess, I got a bit impatient at the end when I discovered I needed to buy yet another part to make this work. For me, this was an appropriate tradeoff.

Hardware

This is the complete expense breakdown:

And this is what it looked liked when it first booted with all the parts installed:

I’ll give some context on the parts below, and after that, I’ll run a couple of quick tests to get some numbers on the efficiency.

HP Z440 Workstation

The Z440 was a simple pick because I already owned it. This was the beginning point. About two years back, I desired a computer that might work as a host for my virtual makers. The Z440 has a Xeon processor with 12 cores, and this one sports 128GB of RAM. Many threads and a great deal of memory, that must work for hosting VMs. I bought it secondhand and after that swapped the 512GB hard drive for a 6TB one to store those virtual devices. 6TB is not required for running LLMs, and for that reason I did not include it in the breakdown. But if you plan to collect lots of models, 512GB may not suffice.

I have actually pertained to like this workstation. It feels all really solid, and I haven’t had any problems with it. At least, until I started this job. It turns out that HP does not like competitors, and I came across some problems when swapping parts.

2 x NVIDIA Tesla P40

This is the magic active ingredient. GPUs are pricey. But, similar to the HP Z440, typically one can find older equipment, that used to be leading of the line and is still very capable, second-hand, for fairly little money. These Teslas were suggested to run in server farms, for things like 3D rendering and other graphic processing. They come geared up with 24GB of VRAM. Nice. They suit a PCI-Express 3.0 x16 slot. The Z440 has 2 of those, so we buy 2. Now we have 48GB of VRAM. Double great.

The catch is the part about that they were implied for servers. They will work fine in the PCIe slots of a typical workstation, however in servers the cooling is handled in a different way. Beefy GPUs take in a great deal of power and can run very hot. That is the factor customer GPUs constantly come geared up with big fans. The cards need to take care of their own cooling. The Teslas, nevertheless, have no fans whatsoever. They get just as hot, but anticipate the server to supply a constant circulation of air to cool them. The enclosure of the card is somewhat shaped like a pipeline, and you have two options: blow in air from one side or blow it in from the opposite. How is that for versatility? You absolutely must blow some air into it, however, or you will harm it as quickly as you put it to work.

The option is simple: just mount a fan on one end of the pipe. And certainly, it appears a whole home industry has actually grown of people that offer 3D-printed shrouds that hold a standard 60mm fan in just the ideal location. The problem is, the cards themselves are already rather bulky, and it is not simple to discover a setup that fits two cards and 2 fan mounts in the computer system case. The seller who sold me my 2 Teslas was kind sufficient to consist of two fans with shrouds, however there was no method I could fit all of those into the case. So what do we do? We purchase more parts.

NZXT C850 Gold

This is where things got irritating. The HP Z440 had a 700 Watt PSU, which may have been enough. But I wasn’t sure, and I needed to purchase a brand-new PSU anyhow due to the fact that it did not have the best connectors to power the Teslas. Using this useful site, I deduced that 850 Watt would be adequate, and I purchased the NZXT C850. It is a modular PSU, indicating that you just need to plug in the cable televisions that you in fact need. It came with a neat bag to save the spare cables. One day, I might give it a great cleansing and use it as a toiletry bag.

Unfortunately, HP does not like things that are not HP, so they made it difficult to swap the PSU. It does not fit physically, and they likewise changed the main board and CPU adapters. All PSU’s I have ever seen in my life are rectangular boxes. The HP PSU also is a rectangle-shaped box, but with a cutout, making certain that none of the normal PSUs will fit. For no technical reason at all. This is simply to mess with you.

The installing was ultimately resolved by using two random holes in the grill that I somehow handled to line up with the screw holes on the NZXT. It sort of hangs stable now, and I feel lucky that this worked. I have seen Youtube videos where individuals turned to double-sided tape.

The connector needed … another purchase.

Not cool HP.

Gainward GT 1030

There is another issue with utilizing server GPUs in this customer workstation. The Teslas are planned to crunch numbers, not to play video games with. Consequently, they don’t have any ports to link a monitor to. The BIOS of the HP Z440 does not like this. It declines to boot if there is no chance to output a video signal. This computer will run headless, but we have no other choice. We have to get a 3rd video card, that we don’t to intent to utilize ever, just to keep the BIOS happy.

This can be the most scrappy card that you can discover, of course, however there is a requirement: we should make it fit on the main board. The Teslas are large and fill the 2 PCIe 3.0 x16 slots. The only slots left that can physically hold a card are one PCIe x4 slot and one PCIe x8 slot. See this site for some background on what those names imply. One can not purchase any x8 card, however, because frequently even when a GPU is advertised as x8, the real adapter on it may be simply as wide as an x16. Electronically it is an x8, physically it is an x16. That will not work on this main board, we really need the small port.

Nvidia Tesla Cooling Fan Kit

As said, the difficulty is to discover a fan shroud that fits in the case. After some browsing, I discovered this kit on Ebay a purchased 2 of them. They came delivered complete with a 40mm fan, and all of it fits perfectly.

Be cautioned that they make a horrible lot of sound. You do not wish to keep a computer system with these fans under your desk.

To watch on the temperature, I whipped up this quick script and put it in a cron task. It regularly reads out the temperature level on the GPUs and sends that to my Homeassistant server:

In Homeassistant I included a chart to the dashboard that displays the values with time:

As one can see, the fans were loud, however not especially reliable. 90 degrees is far too hot. I browsed the web for a sensible upper limitation however could not find anything particular. The documents on the Nvidia site points out a temperature of 47 degrees Celsius. But, what they imply by that is the temperature level of the ambient air surrounding the GPU, not the determined worth on the chip. You understand, the number that in fact is reported. Thanks, Nvidia. That was handy.

After some more searching and checking out the opinions of my fellow web citizens, my guess is that things will be fine, offered that we keep it in the lower 70s. But do not estimate me on that.

My very first effort to treat the scenario was by setting an optimum to the power intake of the GPUs. According to this Reddit thread, one can decrease the power usage of the cards by 45% at the expense of just 15% of the performance. I attempted it and … did not see any distinction at all. I wasn’t sure about the drop in performance, having only a couple of minutes of experience with this setup at that point, however the temperature attributes were certainly the same.

And after that a light bulb flashed on in my head. You see, prior to the GPU fans, there is a fan in the HP Z440 case. In the picture above, it remains in the ideal corner, inside the black box. This is a fan that sucks air into the case, and I figured this would operate in tandem with the GPU fans that blow air into the Teslas. But this case fan was not spinning at all, since the remainder of the computer system did not need any cooling. Checking out the BIOS, I found a setting for the minimum idle speed of the case fans. It ranged from 0 to 6 stars and was presently set to 0. Putting it at a higher setting did marvels for the temperature. It likewise made more noise.

I’ll unwillingly confess that the 3rd video card was handy when changing the BIOS setting.

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