Intel AWS GPU Instance Beats Cheaper Arm Rival for AI Inference Workloads

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AWS offers two budget CUDA GPU instance families — the Arm-based G5g with a Graviton2 CPU and the Intel-based G4dn — both equipped with NVIDIA T4 GPUs and identical VRAM. Although the G5g.xlarge is roughly 20 percent cheaper on demand at $0.42 per hour versus $0.526 for the G4dn.xlarge, a key software incompatibility undermines its value for AI workloads. The vLLM inference framework's official Docker image omits SM 7.5 CUDA kernels from its ARM64 build, meaning the T4G GPU on Arm hosts cannot run optimized inference code that the Intel image supports. Additionally, the G5g.xlarge provides only 8 GB of host RAM compared to 16 GB on the G4dn.xlarge, causing memory allocation failures when loading models like Gemma 4 2B. As a result, the Intel G4dn.xlarge is the more practical and cost-effective choice when measured by deployable AI tokens rather than raw hourly rate.

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