Benchmarking small LLM inference on SageMaker AI: G7 vs G5 and G6
G7 Blackwell vs older GPU tiers: real throughput and cost-per-token data for practitioners choosing inference hardware.
Why it matters
Practitioners evaluating SageMaker for small-model inference get concrete price-performance benchmarks across GPU generations. This is infrastructure decision-making data, not marketing.
The key facts
8 to knowModels tested: Qwen3-Coder-30B, NVIDIA Nemotron-3-Nano-30B (both 30B MoE)
GPU instances compared: G5, G6, G6e, G7 (Blackwell)
Metrics: throughput, latency, cost-per-token
Focus: real-time LLM inference on SageMaker AI
Hardware: NVIDIA Blackwell GPUs in G7 tier
Benchmark: Qwen3-Coder-30B and NVIDIA Nemotron-3-Nano-30B (30B MoE models)
GPU instances tested: G5, G6, G6e, G7 (Blackwell)
Published by AWS (vendor benchmark — credible but incentive-aware)
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: 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…