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Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and G6

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Benchmark two 30B Mixture-of-Experts models, Qwen3-Coder-30B and NVIDIA Nemotron-3-Nano-30B, across G5, G6, G6e, and G7 GPU instances on Amazon SageMaker AI. Compare throughput, latency, and cost-per-token, and see how G7's NVIDIA Blackwell GPUs deliver measurable price-performance gains for real-time LLM inference.

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Choosing the right GPU instance for large language model (LLM) inference is one of the most impactful decisions you make when deploying generative AI at scale. A single generation jump can slash latency, increase throughput, and reduce cost-per-token. However, the real-world magnitude of those gains depends on model architecture, quantization format, and workload shape. In this post, we benchmark two representative 30B Mixture-of-Experts (MoE) models across three GPU instance families on Amazon…

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Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and…