The best GPU for running Llama 3.3 70B Instruct (2026)
Ranked from live rental prices and computed VRAM fit, not opinion. Every card is judged at Q4_K_M — the quantisation most people actually run — at 8k context, so it's a fair comparison. A card that can't fit Llama 3.3 70B Instructat that quality isn't listed, because it could only run a crushed version.
This model's attention shape isn't available yet (its repository is licence-gated), so we can't compute the memory fit needed to rank cards for it.
Check it yourself
See exactly what fits, at any context length
Before you buy
RTX 5090 vs two RTX 3090s
Two 3090s give you 48 GB but not double the speed for chat — llama.cpp's default multi-GPU mode makes the cards take turns. What the benchmarks actually show.
Cheapest way to serve Llama 70B
"Cheapest" flips on duty cycle and concurrency — and in Europe the electricity bill alone can approach the cost of just renting. Plus the config defaults that silently break a 16k deployment.
Is the DGX Spark worth it?
NVIDIA spent three months optimising it and token generation got slower — because 128 GB of memory on a 273 GB/s bus holds huge models and reads them slowly. Who should actually buy one.