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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cloud Native System for LLM Inference Serving · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2507.18007/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2507.18007/feed.xml" rel="self" type="application/rss+xml" /><item><title>Cloud Native System for LLM Inference Serving — HN submission</title><link>https://news.ycombinator.com/item?id=45048646</link><guid isPermaLink="false">urn:hackerpapers:submission:2507.18007:45048646</guid><pubDate>Thu, 28 Aug 2025 05:17:26 GMT</pubDate><description>&lt;p&gt;Ask HN: Do cloud provided LLMs get &amp;quot;dumber&amp;quot; during business hours&lt;/p&gt;&lt;p&gt;I have heard this mentioned, online and in casual conversation ** During business hours these endpoints may get so highly utilised that accuracy and quality decline (ignore latency) (effective available token capacity is reduced etc?** Has anyone run studies/experiments to show (true or false) - across a large dataset - that the performance of these endpoints during peak usage hours vs, low usage hours changes or does not change (I assume some statistical significance test required). I don&amp;#x27;t have the knowledge to answer this question or understand if it&amp;#x27;s a valid hypothesis. Anyone got…&lt;/p&gt;&lt;p&gt;4 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2507.18007/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.DC</category></item></channel></rss>
