Great value for money if you have the time for tinkering and getting the compatibility to work.
I put a datacenter GPU in my gaming PC
131–140 of 199 posts
Re: I put a datacenter GPU in my gaming PC
#132The first dual core processor I built a machine with was an Opteron. It was a nice piece of hardware.
Re: I put a datacenter GPU in my gaming PC
#133Great value for money if you have the time for tinkering and getting the compatibility to work.
and it only gets easier and more defined from here.
Re: I put a datacenter GPU in my gaming PC
#134I also recently decided to buy a datacenter GPU and slap it into a system. Some notes from my experience that the author doesn't mention in their article: Decommissioned NVIDIA V100s and AMD MI50s are fairly cheap, $200 for 16gb and $400-500 for 32gb, for local experimentation. They are also very old. There's an enthusiast community keeping these two cards alive and working with current platforms and models. Nitpick,…
> if given the same treatment a datacenter GPU will overheat itself idling
I have a friend who has learned this through several server grade cards over the years.
Yes your Intel 10G NIC was cheap. No you cannot just stick it in your desktop. It is expecting server level airflow, probably with a cold intake side.
He printed a fan mount, slapped it on, and they’ve been happy together since.
Re: I put a datacenter GPU in my gaming PC
#135> And yes, if you want the absolute best, Opus 4.8 exists. It also costs more per 20 minutes of heavy use than I paid for this entire GPU and adapter setup combined. But the gap is shockingly small. I don't think this is a fair characterization of the situation. I use frontier models via API pre-paid tokens every single day, and I can barely rack up $100 per month . The fact that we figured out how to burn double thi…
> I use frontier models via API pre-paid tokens every single day, and I can barely rack up $100 per month.
According to ccusage (https://github.com/ryoppippi/ccusage) if I didn’t have the 100 USD Max subscription, I’d have to pay Anthropic around 4173 USD for the month of May.
Input │ Output │ Cache Create │ Cache Read │ Total Tokens │ Cost (USD)
1,948,016 │ 19,435,081 │ 103,626,350 │ 6,244,194,278 │ 6,369,203,725 │ $4173.09
Nothing too egregious with my usage patterns, typically Claude Code just churning tasks in 1-2 projects at a time, sometimes while I’m asleep - and I hit around 60-80% of the weekly caps most of the time.
Re: I put a datacenter GPU in my gaming PC
#136I also recently decided to buy a datacenter GPU and slap it into a system. Some notes from my experience that the author doesn't mention in their article: Decommissioned NVIDIA V100s and AMD MI50s are fairly cheap, $200 for 16gb and $400-500 for 32gb, for local experimentation. They are also very old. There's an enthusiast community keeping these two cards alive and working with current platforms and models. Nitpick,…
Did you consider the R9700 or B70 when you went for the MI100? If so, what made you choose the MI100? I've been playing with picking up a card in this class but haven't been able to justify it when running the Qwen3.6 MOE model on a 6800xt is tolerable for the type of projects I've been willing to point local AI at.
I looked at those, the Arc 1100, the w6800, MI50, MI60, v100, v620, and basically anything with 32gb of RAM:
1. I wanted an AMD card.
2. I have an RTX 3090 that's been fun to play with, but I want to get back to using it for gaming.
3. I was looking for between 30-60 tokens/second in terms of performance on the beefier models I want to run. Looking at stock Qwen3 32B the benchmarks reported about 41 tokens/second for MI100. w6800 was 18, MI50 & MI60 could do 60s but had a lot of compromises/special things to achieve that.
4. I used FitMyLLM for some spec-based comparisons (https://www.fitmyllm.com/). The MI100 is roughly double the performance on Qwen 3.5 35B A3B Q5_K_M to the R9700 (462 token/s prefill vs 239 tokens/s, 217 tokens/s vs 118 token/s for inference)
5. I was willing to throw up to $1k at a GPU; I really wanted to throw closer to $650.
To be honest, if money was no objection I would've sprung for a MI210. I also considered the MI250 as they showed up for $1250-1400 with a whopping 128GB, but the PCIE converters for that form factor don't have working AMD drivers yet.
Re: I put a datacenter GPU in my gaming PC
#137This is great! I've been trying to get into local models for a while as I share the sentiment that local models will eventually be so good that there won't be a need to use frontier models for most coding tasks (perhaps that's already true today?).
I have zero experience building computers - where would I even start? I mean, aside from the things already well documented and mentioned in the blog post.
Re: I put a datacenter GPU in my gaming PC
#138> And yes, if you want the absolute best, Opus 4.8 exists. It also costs more per 20 minutes of heavy use than I paid for this entire GPU and adapter setup combined. But the gap is shockingly small. I don't think this is a fair characterization of the situation. I use frontier models via API pre-paid tokens every single day, and I can barely rack up $100 per month . The fact that we figured out how to burn double thi…
> I use frontier models via API pre-paid tokens every single day, and I can barely rack up $100 per month. According to ccusage ( https://github.com/ryoppippi/ccusage ) if I didn’t have the 100 USD Max subscription, I’d have to pay Anthropic around 4173 USD for the month of May. Input │ Output │ Cache Create │ Cache Read │ Total Tokens │ Cost (USD) 1,948,016 │ 19,435,081 │ 103,626,350 │ 6,244,194,278 │ 6,369,203,725…
How do you orchestrate this? I’m on max and would love to be hitting my caps when I’m not actively working a project
Re: I put a datacenter GPU in my gaming PC
#139The AMD MI250X GPUs are also interesting - 128GB of HBM2E at 3TB/s, sometimes you see them second-hand for under $1k, the catch obviously is that it needs an OAM socket. Never seen an easy way to hook them up to a regular mainboard.
This person has built a converter for the OAM socket, but it is only confirmed working with NVIDIA cards at the moment (https://www.reddit.com/r/NVIDIA_SXM2PCIE/comments/1d076cn/oa...)
It fits an MI250X, and the system sees it, but the drivers don't work. They tested an HPE MI250X. There's a rumor on the thread that there are two kinds of MI250X: Ones from HPEs and everyone else's. The HPEs require a special firmware, the normal ones do not. However, the majority of the MI250Xs on the secondhand market are HPE so caveat emptor.
Re: I put a datacenter GPU in my gaming PC
#140Earlier quoted context omitted.
> I use frontier models via API pre-paid tokens every single day, and I can barely rack up $100 per month. According to ccusage ( https://github.com/ryoppippi/ccusage ) if I didn’t have the 100 USD Max subscription, I’d have to pay Anthropic around 4173 USD for the month of May. Input │ Output │ Cache Create │ Cache Read │ Total Tokens │ Cost (USD) 1,948,016 │ 19,435,081 │ 103,626,350 │ 6,244,194,278 │ 6,369,203,725…
How do you orchestrate this? I’m on max and would love to be hitting my caps when I’m not actively working a project
In my case: the Claude Code desktop app makes having a bunch of parallel sessions easy, at least compared to when I had just a bunch of terminal windows open https://claude.com/download can also couple that with Remote Control https://code.claude.com/docs/en/remote-control
Previously I still had the issue of it occasionally stopping let's say after Stage 2/7 is done in some plan and asking me to continue, though I was asleep. The options there were either looping it (like RALPH loop), or more recently they also released their dynamic workflows alongside Opus 4.8: https://claude.com/blog/introducing-dynamic-workflows-in-cla... and now I just use that.
So essentially you come up with a plan and just ask it to create a dynamic workflow for you, and it's gonna go through everything step by step, sometimes parallelizing (as it normally would with sub-agents) as necessary. Can also use worktrees if needed.
Here's an example of the UI: https://imgur.com/a/4Gr3Z2T (note that I'm using DeepSeek there for a small local utility, with a tool I'm using for managing various providers with Claude Code, but works the same with subscription)
I looked at the stuff Cline was doing with their Kanban boards too, but in the end realized that I don't really need those (for now) and that Claude Code is enough.