Out of sheer curiosity: What’s required for the average Joe to use this, even at a glacial pace, in terms of hardware? Or is it even possible without using smart person magic to append enchanted numbers and make it smaller for us masses?
Your 1.58-bit dynamic quant model is a religious experience, even at one or two tokens per second (which is what I get on my 128 MB Raptor Lake+4090). It's like owning your own genie... just ridiculously smart. Thanks for the work you've put into it!
Likewise - for me, it feels how I imagined getting a microcomputer in the 70s was like. (Including the hit to the wallet… an Apple II cost the 2024 equivalent of ~$5k, too.)
You can run the 4bit quantized version of it on a M3 Ultra 512GB. That's quite expensive though. Another alternative is a fast CPU with 500GB of DDR5 RAM. That of course, is also not cheap and slower than the M3 Ultra. Or, you buy multiple Nvidia cards to reach ~500GB of VRam. That is probably the most expensive option but also the fastest
Vast.ai has a bunch of 1x H100 SXM available, right now the cheapest at $1.554/hr.
Not affiliated, just a (mostly) happy user, although don't trust the bandwidth numbers, lots of variance (not surprising though, it is a user-to-user marketplace).
Every time someone asks me what hardware to buy to run these at home I show them how many thousands of hours at vast.ai you could get for the same cost.
I don't even know how these Vast servers make money because there is no way you can ever pay off your hardware from the pennies you're getting.
Worth mentioning that a single H100 (80-96GB) is not enough to run R1. You're looking at 6-8 GPUs on the lower end, and factor in the setup and download time.
An alternative is to use serverless GPU or LLM providers which abstract some of this for you, albeit at a higher cost and slow starts when you first use your model for some time.
About 768 gigs of ddr5 RAM in a dual socket server board with 12 channel memory and an extra 16 gig or better GPU for prompt processing. It's a few grand just to run this thing at 8-10 tokens/s
About $8000 plus the GPU. Let's throw in a 4080 for about $1k, and you have the full setup for the price of 3 RTX5090. Or cheaper than a single A100. That's not a bad deal.
For the hobby version you would presumably buy a used server and a used GPU. DDR4 ECC Ram can be had for a little over $1/GB, so you could probably build the whole thing for around $2k
Been putting together a "mining rig" [1] (or rather I was before the tariffs, ha ha.) Going to try to add a 2nd GPU soon. (And I should try these quantized versions.)
Mobo was some kind of mining rig from AliExpress for less than $100. GPU is an inexpensive NVIDIA TESLA card that I 3D printed a shroud for (added fans). Power supply a cheap 2000 Watt Dell server PS off eBay....
Thats how a lot of application layer startups are going to make money. There is a bunch of high quality usage data. Either you monetize it yourself (cursor), get acquired (windsurf) or provide that data to others at a fee (lmsys, mercor). This is inevitable and a market for this is just going to increaase. If you want to prevent this as an org, there arent many ways out. Either use open source models you can deploy, or deal directly with model providers where you can sign specific contracts.
And you are getting something valuable in return. It's probably a good trade for many, especially when they are doing something like summarizing a public article.
I'm not so sure. I have agents that do categorization work. Take a title, drill through a browse tree to find the most applicable leaf category. Lots of other classification tasks that are not particularly sensitive and it's hard to imagine them being very good for training. Also transformations of anonymized numerical data, parsing, etc.
Practically, smaller, quantized versions of R1 can be run on a pretty typically Macbook Pro setup. Quantized versions are definitely less performant, but they will absolutely run.
Truthfully, it's just not worth it. You either run these things so slowly that you're wasting your time or you have to buy 4- or 5-figures of hardware that's going to sit, mostly unused.
As mentioned you can run this on a server board with 768+ gb memory in cpu mode. Average joe is going to be running quantized 30b (not 600b+) models on an $300/$400/$900 8/12/16gb GPU
You can pay Amazon to do it for you at about a penny per 10 thousand tokens.
There's a couple of guides for setting it up "manually" on ec2 instances so you're not paying the Bedrock per-token-prices, here's [1] that states four g6e.48xlarge instances (192 vCPUs, 1536GB RAM, 8x L40S Tensor Core GPUs that come with 48 GB of memory per GPU)
Quick google tells me that g6e.48xlarge is something like 22k USD per month?
Sorry I'm being cheeky here, but realistically unless you want to shell out 10k for the equivalent of a Mac Studio with 512GB of RAM, you are best using other services or a small distilled model based on this one.
If speed is truly not an issue, you can run Deepseek on pretty much any PC with a large enough swap file, at a speed of about one token every 10 minutes assuming a plain old HDD.
Something more reasonable would be a used server CPU with as many memory channels as possible and DDR4 ram for less than $2000.
But before spending big, it might be a good idea to rent a server to get a feel for it.
