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Hardware for local LLMs
GPUs and unified-memory systems ranked for running downloadable models — memory, bandwidth, max model, estimated tokens/sec.
Consumer NVIDIA GeForce RTX 5090
Consumer NVIDIA GeForce RTX 4090
Consumer NVIDIA GeForce RTX 3090 Ti
Consumer NVIDIA GeForce RTX 5080
Consumer NVIDIA GeForce RTX 3090
Consumer NVIDIA GeForce RTX 3080 Ti
Consumer NVIDIA GeForce RTX 5070 Ti
Consumer NVIDIA GeForce RTX 3080 10GB
Consumer NVIDIA GeForce RTX 4080
Consumer NVIDIA GeForce RTX 4070 Ti Super
Consumer NVIDIA GeForce RTX 5070
Consumer NVIDIA GeForce RTX 3070 Ti
Consumer NVIDIA GeForce RTX 4070 Super
Consumer NVIDIA GeForce RTX 4070
Consumer NVIDIA GeForce RTX 5060 Ti 16GB
Consumer NVIDIA GeForce RTX 5060 Ti 8GB
Consumer NVIDIA GeForce RTX 3070
Consumer NVIDIA GeForce RTX 4060 Ti 16GB
Consumer NVIDIA GeForce RTX 4060 Ti 8GB
NVIDIA GeForce RTX 2050
NVIDIA GeForce RTX 2050 Mobile
Prosumer NVIDIA RTX PRO 6000 Blackwell
Prosumer NVIDIA RTX 6000 Ada 48GB
Prosumer NVIDIA DGX Spark
SME NVIDIA H100 PCIe 80GB
SME NVIDIA A100 PCIe 80GB
SME NVIDIA L40S 48GB
Enterprise NVIDIA B200
Enterprise NVIDIA H200
Enterprise NVIDIA H100 SXM5 80GB
Enterprise NVIDIA A100 SXM4 80GB
How to read this
Two numbers dominate local inference: memory (how big a model + context fits) and bandwidth (token speed). Click any hardware for the full size×quant matrix, max usable context and measured reports, or browse runtimes.