What's the cheapest way to run a 70B model: used GPUs, a Mac or renting?

The cheapest way to run a 70B model is to rent a 48GB GPU by the hour. On November 3, 2026 Runpod listed an RTX A6000 (48GB) at $0.33 an hour on its Community Cloud and $0.59 on its Secure Cloud, and Vast.ai had one from $0.40 an hour, with nothing to buy. If you'll run a 70B model most days for years, the cheapest hardware you can own is two used RTX 3090s at about $1,000 each; against renting, the cards pay for themselves after roughly 3,400 to 6,100 hours. A Mac Studio with 64GB starts at $3,499 on Apple's store: it's the quiet, one-box option, not the cheap one.

How much memory does a 70B model need?

About 42.5GB at the usual 4-bit setting, plus a few GB for context. The most-downloaded way to run Llama 3.3 70B at home is a GGUF file, and in bartowski's file table on Hugging Face the Q4_K_M file, marked "Good quality, default size for most use cases", is 42.52GB. Smaller 4-bit files exist: IQ4_XS is 37.90GB. The memory for your conversation (the context) comes on top, so plan on about 48GB of total GPU or unified memory. Our VRAM calculator shows the exact fit for your context length.

That rules out every single consumer graphics card: the biggest common ones have 24GB or 32GB. So there are three real routes to 48GB: two used 24GB cards, a Mac with enough unified memory, or a rented data-center card.

Cost of each way, side by side

Is renting the cheapest way to run a 70B model?

Yes, unless you use it for thousands of hours. You pay only while the machine is on, and one 48GB card holds the whole Q4 model, so there's nothing to split. At 12:20 UTC on November 3, 2026, our price tracker read an RTX A6000 (48GB) on Vast.ai from $0.40 an hour on-demand (median $0.46 across seven offers; interruptible spot from $0.24). Runpod's pricing page listed the RTX A6000 at $0.33 an hour on Community Cloud and $0.59 on Secure Cloud; the A40, also 48GB, was $0.35 and $0.59. Today's prices are on our cloud GPU price table, refreshed every hour.

Two things to know before you rent:

• Check the memory on the listing. Vast.ai lists some 48GB cards, like the A40 and L40S, at 45GB usable in our tracker, and it sells both 40GB and 80GB versions of the A100. A 40GB card won't hold a 42.5GB model. An 80GB card has plenty of room but costs more: Runpod listed the A100 80GB at $1.19 an hour on Community Cloud and $1.79 on Secure Cloud on Nov 3.
• Stopped isn't always free. Storage can keep billing while a machine is stopped, so delete it when you're done. Our Vast.ai review and Runpod review cover the billing details.

Are two used RTX 3090s cheaper than renting?

Only if you'll use them for thousands of hours. Two 3090s give you 48GB, enough for the Q4 model, and they're the cheapest way to own that much GPU memory. Hardware Corner's RTX 3090 page showed a current US price of $1,000 (average market value) when we read it on November 3, 2026; the page doesn't date that figure. Used prices have been climbing with the memory shortage, so treat $1,000 as a rough guide and check recently sold listings on the day you buy, and see our used RTX 3090 buying guide for the condition checks.

The break-even is simple division. Two cards at $1,000 each are $2,000:

At 4 hours a day, 3,400 hours is about two and a third years, 5,000 hours about three and a half, and 6,100 hours about four. At 8 hours a day it's 14 to 25 months. And that's before the rest of the PC, which the cards need: a motherboard with two well-spaced PCIe slots, a power supply big enough for two high-power cards (see what PSU you need), a case with real airflow, and the electricity bill. If you don't already own most of that, the break-even moves further out. Splitting a model across two cards also needs software that supports it; llama.cpp does, and our guide on whether you need two GPUs covers the trade-offs.

Is a Mac Studio a cheap way to run a 70B model?

No. It's the easiest way, not the cheapest. A Mac runs the model from unified memory, so there's no second card to wire up, and it's quiet. On Apple's store on November 3, 2026, the Mac Studio with the M5 Max (18-core CPU, 40-core GPU) and 64GB of memory was $3,799 with 1TB of storage; dropping to 512GB of storage takes $300 off, so $3,499 is the cheapest 64GB Mac Studio. The cheapest Mac Studio, $2,499, has 36GB, which isn't enough. 128GB on the M5 Max is a $1,600 upgrade, and the M5 Ultra starts at $5,499 with 96GB.

Two honest limits. First, 64GB is snug: macOS keeps part of the memory for itself and the GPU can't use all of it, so a 42.5GB model leaves modest room for long conversations. A smaller 4-bit file like IQ4_XS (37.90GB) gives you breathing room. Second, speed: generating each word means reading the whole model from memory, and Apple's spec page lists 614GB/s of memory bandwidth for the 40-core M5 Max. Divide that by 42.5GB and the theoretical ceiling is about 14 words (tokens) a second, and real speeds come in below that. The M5 Ultra's 1.2TB/s doubles it, at $5,499 and up. Our Mac Studio vs NVIDIA comparison has measured speeds.

Against renting, $3,499 buys about 5,900 hours of a $0.59 Runpod Secure Cloud A6000, or about 10,600 hours at the $0.33 Community Cloud rate. If silence, power draw and one box matter to you, that trade can be worth it. On cost alone, the Mac doesn't win.

What does each way cost after six months?

Rental figures are machine time only; storage and electricity are extra on the respective sides. Hardware keeps its value too: a used 3090 can be resold, and a rental bill can't.

Are there other cheap ways to run a 70B model?

A few, each with a real catch:

• One 24GB card with a 2-bit file. bartowski's IQ2_XS file is 21.14GB, so it fits on one 3090, but 2-bit quantization costs noticeable quality. See what quantization does.
• A 128GB unified-memory mini PC. AMD's Ryzen AI Max+ 395 ("Strix Halo") machines and NVIDIA's DGX Spark hold a 70B model easily but have less memory bandwidth than a Mac Studio, so dense 70B models run slowly. See Strix Halo and is the DGX Spark worth it.
• Your CPU and system RAM. If your PC already has 64GB of RAM, llama.cpp can run a Q4 70B model with no GPU at all. It costs nothing extra and is very slow: fine for a test, painful for chat.
• Old server cards. Used data-center cards like the Tesla P40 (24GB) sell for less than a 3090 but have no display output, need their own cooling and run older software; see is a used Tesla P40 worth it.

For renting a bigger card for long contexts or serving, see the cheapest way to run Llama 70B in the cloud, and the live per-hour cost of this exact model is on cost to run Llama 3.3 70B.

The short version: rent a 48GB card to run a 70B model today, and buy hardware only once you know you'll use it every day. Today's rental prices are on our cloud GPU table.