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g5g vs g6 for LLM Serving: the Same Code, and 3.7x the Throughput

This story is from 2026-08-31. It is preserved in the archive; the latest stories are on the live feed.

This article compares two AWS GPU instance families for serving a small language model, using a payload that is byte-identical on both. The older family loses 87% of decode to dtype conversion, and nothing in any log, metric or health check says so. The code is here: https://github.com/xbill9/gemma…

Read the full story at DEV Community — Machine Learning ↗

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  1. 2026-08-31 01:40 · DEV Community — Machine Learning
    g5g vs g6 for LLM Serving: the Same Code, and 3.7x the Throughput

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