Use cases by GPU model

LLM training, high-throughput inference, HPC. 80 GB HBM3, 3,350 GB/s bandwidth.

Production AI workhorse. 80 GB HBM2e, mature CUDA ecosystem, widest cloud availability.

Best-value inference GPU. 48 GB GDDR6, strong FP32 for generative AI.

Consumer Ada GPU. 24 GB GDDR6X for fine-tuning, inference, and image generation.

48 GB GDDR6 data-center GPU for visualization, mid-size inference, and virtual workstations.

Power-efficient inference. 24 GB GDDR6, 150W TDP. Primary GPU in AWS g5 instances.

Budget 24 GB VRAM option for inference, fine-tuning, and experimentation.

Most cost-effective inference GPU. 16 GB GDDR6, 70W TDP, widely available on GCP and AWS.

Ada Lovelace efficiency. 24 GB GDDR6, 72W TDP for edge and high-density inference.

AMD CDNA 3. 192 GB HBM3, 5,300 GB/s bandwidth for memory-bound LLM inference.