Hardware for local AI

Hardware guide

Compare machines before choosing a local AI path

This table compares common PCs, GPUs, unified-memory Macs and datacenter systems for local AI work. Use it to estimate which machines are realistic for learning, single-user experiments, multi-session serving or large-scale inference.

Memory capacity decides what can fit. Memory bandwidth is a rough signal for generation speed, but real LLM performance also depends on the runtime, quantization, context length and concurrency.

Before buying hardware: verify the selected hardware against the models, runtime, quantization, context length and concurrency you plan to use. Treat these estimates as a starting point, then check recent hands-on tests, benchmarks and videos for that setup.

Local AI hardware reference list
Hardware Memory Bandwidth Computing power vLLM
RTX 3060 12GBNVIDIA GeForce RTX 3060 12 GB desktop GPU 12 GBGPU VRAM 360 GB/s ~101 TOPS yes
DDR4 16GB ComputerComputer with 16 GB DDR4-3200 dual-channel RAM 16 GBRAM 51.2 GB/s ~2 TOPS no
DDR5 16GB ComputerComputer with 16 GB DDR5-5600 dual-channel RAM 16 GBRAM 89.6 GB/s ~3 TOPS no
RTX 2000 AdaNVIDIA RTX 2000 Ada Generation 16 GB 16 GBGPU VRAM 224 GB/s ~191.9 TOPS yes
RTX 4060 Ti 16GBLow-cost NVIDIA 16 GB VRAM desktop GPU baseline 16 GBGPU VRAM 288 GB/s ~353 TOPS yes
RTX 5060 Ti 16GBCurrent low-cost NVIDIA 16 GB VRAM desktop GPU class 16 GBGPU VRAM 448 GB/s ~759 TOPS yes
RTX 5080NVIDIA GeForce RTX 5080 16 GB 16 GBGPU VRAM 960 GB/s ~1801 TOPS yes
Mac mini M4Apple Mac mini M4 system with 24 GB unified memory 24 GBUnified RAM 120 GB/s ~40 TOPS no
M4 ProApple M4 Pro with 24 GB unified memory 24 GBUnified RAM 273 GB/s not available no
RTX 3090 TiNVIDIA GeForce RTX 3090 Ti 24 GB 24 GBGPU VRAM 1008 GB/s ~320 TOPS yes
DDR5 32GB ComputerComputer with 32 GB DDR5-5600 dual-channel RAM 32 GBRAM 89.6 GB/s ~3 TOPS no
RTX 5090NVIDIA GeForce RTX 5090 32 GB desktop GPU class 32 GBGPU VRAM 1792 GB/s ~3352 TOPS yes
M5 ProApple MacBook Pro M5 Pro 20-core GPU configuration with large unified memory 64 GBUnified RAM 307 GB/s ~180 TOPS no
Radeon 8060S 96GBAMD Radeon 8060S Graphics with 96 GB allocated unified memory 96 GBUnified RAM 256 GB/s not available yes
M3 UltraApple Mac Studio M3 Ultra 80-core GPU configuration with 96 GB unified memory 96 GBUnified RAM 819 GB/s ~120 TOPS no
RTX PRO 6000NVIDIA RTX PRO 6000 Blackwell series 96 GBGPU VRAM 1792 GB/s ~3511 TOPS yes
DGX SparkNVIDIA DGX Spark desktop AI system with unified memory 128 GBUnified RAM 273 GB/s ~1000 TOPS yes
M5 MaxApple MacBook Pro M5 Max 40-core GPU configuration 128 GBUnified RAM 614 GB/s ~320 TOPS no
M5 UltraApple Mac Studio M5 Ultra 80-core GPU configuration with 256 GB unified 256 GBUnified RAM 1200 GB/s ~540 TOPS no
DGX StationNVIDIA DGX Station with GB300 Grace Blackwell Ultra 748 GBCoherent Memory 7100 GB/s ~20000 TOPS yes
ET900N G3ASUS ExpertCenter Pro ET900N G3 with NVIDIA GB300 Grace Blackwell Ultra 748 GBCoherent Memory 7100 GB/s ~20000 TOPS yes
DGX H200NVIDIA 8-GPU Hopper rackmount AI system with 1,128 GB total HBM3e, 141 GB per GPU and 4.8 TB/s HBM bandwidth per GPU 1128 GBGPU HBM3e 4800 GB/s ~3958 TOPS yes
DGX B200NVIDIA 8-GPU Blackwell rackmount AI system with 1,440 GB total HBM3e, 180 GB per GPU and 64 TB/s aggregate HBM bandwidth 1440 GBGPU HBM3e 8000 GB/s ~18000 TOPS yes
GB200 NVL72NVIDIA rack-scale liquid-cooled system with 72 Blackwell GPUs, 36 Grace CPUs, 13.4 TB total HBM3e, 576 TB/s aggregate HBM bandwidth and 130 TB/s aggregate NVLink 13400 GBGPU HBM3e 8000 GB/s ~20000 TOPS yes
GB300 NVL72NVIDIA rack-scale liquid-cooled system with 72 Blackwell Ultra GPUs, 36 Grace CPUs, about 20 TB total HBM3e, up to 576 TB/s aggregate HBM bandwidth and 130 TB/s aggregate NVLink 20000 GBGPU HBM3e 8000 GB/s ~20000 TOPS yes

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