Updated October 2026
Best GPU for local AI at three budgets
VRAM decides what you can run; bandwidth decides how fast. The cards that make sense in late 2026, when a new 24GB card under $3,000 doesn't exist and the used market is where the value is.
As an Amazon Associate I earn from qualifying purchases. Product links on this page go to Amazon; they are affiliate links, and the price you pay is the same.
The picks
NVIDIA GeForce RTX 5070 Ti (16GB)
The best new 16GB card with CUDA under the budget line. Runs 14B models fast and 30B models at tighter quantization. Plan to want more VRAM within a year.
The best new 16GB card you can buy under the budget line while 24GB cards sit above it. CUDA means every tool just works.
NVIDIA GeForce RTX 5060 Ti (16GB)
Cheapest way to 16GB with CUDA. Slower than the 5070 Ti, holds the same models. Make sure it's the 16GB version.
For local LLMs, holding the model matters more than speed. This is the lowest price of entry to 16GB with CUDA. Get the 16GB version; the 8GB one is useless for this.
AMD Radeon RX 7900 XTX (24GB, used)
The only 24GB card near the budget line, used. Linux and a ROCm-tested stack only; if that sentence worried you, skip it.
Only worth it if you've checked that your stack runs on ROCm. If it does, this is the cheapest 24GB card in existence right now.
NVIDIA GeForce RTX 3090 (24GB, renewed)
Still the most VRAM per dollar in an NVIDIA card. Buy renewed with a warranty, check that your power supply has two 8-pin connectors to spare.
For LLM inference, VRAM capacity matters more than compute. Two of these give you 48GB for less than one 5090.
NVIDIA GeForce RTX 4090 (24GB, used or renewed)
24GB and much faster than the 3090, used or renewed only since production ended. The pick if you want 24GB and speed without 5090 money.
Mature drivers, huge community, and 24GB covers most of what people actually run. Buy renewed with a warranty; the price has held because local AI buyers want exactly this card.
NVIDIA GeForce RTX 5090 (32GB)
32GB and nearly 1.8TB/s of bandwidth, at roughly twice its launch price in 2026. Needs a 1000W supply and a case with real airflow.
Memory bandwidth near 1.8TB/s. Tokens per second on a 32B model are in a different league from anything below it.
The one rule
VRAM capacity first, everything else second. A model that doesn’t fit in VRAM spills into system RAM and runs ten times slower. A model that fits on a slow card beats a model that doesn’t fit on a fast one. So the question is never “which card is fastest,” it’s “which card holds the models I want to run.”
Rough sizes at 4-bit quantization:
- 8B model: 5GB. Any 8GB card.
- 14B model: 9GB. 12GB card minimum, 16GB comfortable.
- 30B class: 18 to 20GB. 24GB card.
- 70B class: 40GB. Two 24GB cards, or a Mac, or CPU offload and patience.
The 2026 market, in one paragraph
A memory shortage has pushed every card up. The RTX 5090 sells for about double its launch price, the RTX 4090 is out of production and trades used for more than it cost new, and even a used RTX 3090 costs more than it did in 2024. The practical effect: there is no new 24GB card under $3,000. Under $1,000 buys a new 16GB card; $1,000 to $3,000 buys a used 24GB NVIDIA card; a new 32GB card is No ceiling money. The tiers on this page reflect that, not the launch prices you may remember.
NVIDIA or AMD
NVIDIA. Not because AMD cards are bad, but because every AI tool is written for CUDA first and ROCm second, and “second” sometimes means “not yet” or “not on Windows.” If you already run Linux and have checked that your specific stack supports ROCm, a used RX 7900 XTX is the only 24GB card anywhere near the budget line and worth a look. Otherwise, the time you save with CUDA is worth more than the money you save with AMD.
Why the used 3090 is still on this list
It launched in 2020, it’s slow by today’s standards, and it has 24GB of VRAM. For running models, that last fact outweighs the first two. Two renewed 3090s give you 48GB for less than one 5090 and let you load a 70B model across both. Check the seller’s warranty terms and plan for 350W per card.
The 16GB question
A 5070 Ti or a 5060 Ti 16GB is the realistic entry point if you want a new card and can’t stretch to a used 24GB one. Either runs 14B models fast and 30B models at tighter quantization with some quality loss. Neither is a long-term card for this; you’ll want more VRAM within a year. The 5060 Ti holds the same models at lower speed for less money; the 5070 Ti is the one to get if the budget allows.
Should you wait for the RTX 50 Super?
Maybe. The rumored Super refresh brings 24GB to the 5070 Ti and 5080 class, which would create the new-24GB-under-$1,500 card this page says doesn’t exist. As of October 2026 it has slipped to a January 2027 target. The wait-or-buy guide has the details and what to buy if you can’t wait.
Power and case
A 4090 or 5090 wants a 1000W ATX 3.1 supply with a native 12V-2x6 connector. Adapters work but they’re the number one source of melted connectors. The card is also three slots wide and 30cm long; measure your case. A 5070 Ti or 5060 Ti runs happily on 850W.